Search Results for author: Jiashi Feng

Found 311 papers, 129 papers with code

PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator

1 code implementation13 May 2024 Hanshu Yan, Xingchao Liu, Jiachun Pan, Jun Hao Liew, Qiang Liu, Jiashi Feng

We present Piecewise Rectified Flow (PeRFlow), a flow-based method for accelerating diffusion models.

StoryDiffusion: Consistent Self-Attention for Long-Range Image and Video Generation

1 code implementation2 May 2024 Yupeng Zhou, Daquan Zhou, Ming-Ming Cheng, Jiashi Feng, Qibin Hou

This module converts the generated sequence of images into videos with smooth transitions and consistent subjects that are significantly more stable than the modules based on latent spaces only, especially in the context of long video generation.

motion prediction Story Generation +1

Magic-Boost: Boost 3D Generation with Mutli-View Conditioned Diffusion

no code implementations9 Apr 2024 Fan Yang, Jianfeng Zhang, Yichun Shi, Bowen Chen, Chenxu Zhang, Huichao Zhang, Xiaofeng Yang, Jiashi Feng, Guosheng Lin

Benefiting from the rapid development of 2D diffusion models, 3D content creation has made significant progress recently.

3D Generation

Magic-Me: Identity-Specific Video Customized Diffusion

1 code implementation14 Feb 2024 Ze Ma, Daquan Zhou, Chun-Hsiao Yeh, Xue-She Wang, Xiuyu Li, Huanrui Yang, Zhen Dong, Kurt Keutzer, Jiashi Feng

To achieve this, we propose three novel components that are essential for high-quality identity preservation and stable video generation: 1) a noise initialization method with 3D Gaussian Noise Prior for better inter-frame stability; 2) an ID module based on extended Textual Inversion trained with the cropped identity to disentangle the ID information from the background 3) Face VCD and Tiled VCD modules to reinforce faces and upscale the video to higher resolution while preserving the identity's features.

Text-to-Image Generation Video Generation

Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data

3 code implementations19 Jan 2024 Lihe Yang, Bingyi Kang, Zilong Huang, Xiaogang Xu, Jiashi Feng, Hengshuang Zhao

To this end, we scale up the dataset by designing a data engine to collect and automatically annotate large-scale unlabeled data (~62M), which significantly enlarges the data coverage and thus is able to reduce the generalization error.

Ranked #3 on Monocular Depth Estimation on NYU-Depth V2 (using extra training data)

Data Augmentation Monocular Depth Estimation +1

MagicVideo-V2: Multi-Stage High-Aesthetic Video Generation

no code implementations9 Jan 2024 Weimin WANG, Jiawei Liu, Zhijie Lin, Jiangqiao Yan, Shuo Chen, Chetwin Low, Tuyen Hoang, Jie Wu, Jun Hao Liew, Hanshu Yan, Daquan Zhou, Jiashi Feng

The growing demand for high-fidelity video generation from textual descriptions has catalyzed significant research in this field.

MORPH Video Generation

Harnessing Diffusion Models for Visual Perception with Meta Prompts

1 code implementation22 Dec 2023 Qiang Wan, Zilong Huang, Bingyi Kang, Jiashi Feng, Li Zhang

Our key insight is to introduce learnable embeddings (meta prompts) to the pre-trained diffusion models to extract proper features for perception.

Ranked #2 on Semantic Segmentation on Cityscapes test (using extra training data)

Monocular Depth Estimation Pose Estimation +1

Video Recognition in Portrait Mode

1 code implementation21 Dec 2023 Mingfei Han, Linjie Yang, Xiaojie Jin, Jiashi Feng, Xiaojun Chang, Heng Wang

While existing datasets mainly comprise landscape mode videos, our paper seeks to introduce portrait mode videos to the research community and highlight the unique challenges associated with this video format.

Data Augmentation Video Recognition

Towards Accurate Guided Diffusion Sampling through Symplectic Adjoint Method

1 code implementation19 Dec 2023 Jiachun Pan, Hanshu Yan, Jun Hao Liew, Jiashi Feng, Vincent Y. F. Tan

However, since the off-the-shelf pre-trained networks are trained on clean images, the one-step estimation procedure of the clean image may be inaccurate, especially in the early stages of the generation process in diffusion models.

Video Generation

Vista-LLaMA: Reliable Video Narrator via Equal Distance to Visual Tokens

no code implementations12 Dec 2023 Fan Ma, Xiaojie Jin, Heng Wang, Yuchen Xian, Jiashi Feng, Yi Yang

This amplifies the effect of visual tokens on text generation, especially when the relative distance is longer between visual and text tokens.

Hallucination Position +2

PixelLM: Pixel Reasoning with Large Multimodal Model

no code implementations4 Dec 2023 Zhongwei Ren, Zhicheng Huang, Yunchao Wei, Yao Zhao, Dongmei Fu, Jiashi Feng, Xiaojie Jin

PixelLM excels across various pixel-level image reasoning and understanding tasks, outperforming well-established methods in multiple benchmarks, including MUSE, single- and multi-referring segmentation.

Decoder Segmentation

AvatarStudio: High-fidelity and Animatable 3D Avatar Creation from Text

no code implementations29 Nov 2023 Jianfeng Zhang, Xuanmeng Zhang, Huichao Zhang, Jun Hao Liew, Chenxu Zhang, Yi Yang, Jiashi Feng

We study the problem of creating high-fidelity and animatable 3D avatars from only textual descriptions.

MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model

2 code implementations27 Nov 2023 Zhongcong Xu, Jianfeng Zhang, Jun Hao Liew, Hanshu Yan, Jia-Wei Liu, Chenxu Zhang, Jiashi Feng, Mike Zheng Shou

Existing animation works typically employ the frame-warping technique to animate the reference image towards the target motion.

Image Animation

MAgIC: Investigation of Large Language Model Powered Multi-Agent in Cognition, Adaptability, Rationality and Collaboration

1 code implementation14 Nov 2023 Lin Xu, Zhiyuan Hu, Daquan Zhou, Hongyu Ren, Zhen Dong, Kurt Keutzer, See Kiong Ng, Jiashi Feng

Large Language Models (LLMs) have marked a significant advancement in the field of natural language processing, demonstrating exceptional capabilities in reasoning, tool usage, and memory.

Benchmarking Language Modelling +1

ChatAnything: Facetime Chat with LLM-Enhanced Personas

no code implementations12 Nov 2023 Yilin Zhao, Xinbin Yuan, ShangHua Gao, Zhijie Lin, Qibin Hou, Jiashi Feng, Daquan Zhou

For MoV, we utilize the text-to-speech (TTS) algorithms with a variety of pre-defined tones and select the most matching one based on the user-provided text description automatically.

In-Context Learning Novel Concepts +2

EPIM: Efficient Processing-In-Memory Accelerators based on Epitome

no code implementations12 Nov 2023 Chenyu Wang, Zhen Dong, Daquan Zhou, Zhenhua Zhu, Yu Wang, Jiashi Feng, Kurt Keutzer

On the hardware side, we modify the datapath of current PIM accelerators to accommodate epitomes and implement a feature map reuse technique to reduce computation cost.

Model Compression Neural Architecture Search +1

Low-Resolution Self-Attention for Semantic Segmentation

no code implementations8 Oct 2023 Yu-Huan Wu, Shi-Chen Zhang, Yun Liu, Le Zhang, Xin Zhan, Daquan Zhou, Jiashi Feng, Ming-Ming Cheng, Liangli Zhen

Semantic segmentation tasks naturally require high-resolution information for pixel-wise segmentation and global context information for class prediction.

Decoder Segmentation +1

GETAvatar: Generative Textured Meshes for Animatable Human Avatars

no code implementations ICCV 2023 Xuanmeng Zhang, Jianfeng Zhang, Rohan Chacko, Hongyi Xu, Guoxian Song, Yi Yang, Jiashi Feng

We study the problem of 3D-aware full-body human generation, aiming at creating animatable human avatars with high-quality textures and geometries.

Image Generation

MaskDiffusion: Boosting Text-to-Image Consistency with Conditional Mask

no code implementations8 Sep 2023 Yupeng Zhou, Daquan Zhou, Zuo-Liang Zhu, Yaxing Wang, Qibin Hou, Jiashi Feng

In this work, we identify that a crucial factor leading to the text-image mismatch issue is the inadequate cross-modality relation learning between the prompt and the output image.

MagicAvatar: Multimodal Avatar Generation and Animation

no code implementations28 Aug 2023 Jianfeng Zhang, Hanshu Yan, Zhongcong Xu, Jiashi Feng, Jun Hao Liew

This report presents MagicAvatar, a framework for multimodal video generation and animation of human avatars.

Video Generation

MagicEdit: High-Fidelity and Temporally Coherent Video Editing

no code implementations28 Aug 2023 Jun Hao Liew, Hanshu Yan, Jianfeng Zhang, Zhongcong Xu, Jiashi Feng

In this report, we present MagicEdit, a surprisingly simple yet effective solution to the text-guided video editing task.

Translation Video Editing

Dataset Quantization

1 code implementation ICCV 2023 Daquan Zhou, Kai Wang, Jianyang Gu, Xiangyu Peng, Dongze Lian, Yifan Zhang, Yang You, Jiashi Feng

Extensive experiments demonstrate that DQ is able to generate condensed small datasets for training unseen network architectures with state-of-the-art compression ratios for lossless model training.

object-detection Object Detection +2

AdjointDPM: Adjoint Sensitivity Method for Gradient Backpropagation of Diffusion Probabilistic Models

1 code implementation20 Jul 2023 Jiachun Pan, Jun Hao Liew, Vincent Y. F. Tan, Jiashi Feng, Hanshu Yan

Existing customization methods require access to multiple reference examples to align pre-trained diffusion probabilistic models (DPMs) with user-provided concepts.

Denoising

BuboGPT: Enabling Visual Grounding in Multi-Modal LLMs

1 code implementation17 Jul 2023 Yang Zhao, Zhijie Lin, Daquan Zhou, Zilong Huang, Jiashi Feng, Bingyi Kang

Our experiments show that BuboGPT achieves impressive multi-modality understanding and visual grounding abilities during the interaction with human.

Instruction Following Sentence +1

COSA: Concatenated Sample Pretrained Vision-Language Foundation Model

1 code implementation15 Jun 2023 Sihan Chen, Xingjian He, Handong Li, Xiaojie Jin, Jiashi Feng, Jing Liu

Due to the limited scale and quality of video-text training corpus, most vision-language foundation models employ image-text datasets for pretraining and primarily focus on modeling visually semantic representations while disregarding temporal semantic representations and correlations.

 Ranked #1 on TGIF-Frame on TGIF-QA (using extra training data)

Question Answering Retrieval +6

Delving Deeper into Data Scaling in Masked Image Modeling

no code implementations24 May 2023 Cheng-Ze Lu, Xiaojie Jin, Qibin Hou, Jun Hao Liew, Ming-Ming Cheng, Jiashi Feng

The study reveals that: 1) MIM can be viewed as an effective method to improve the model capacity when the scale of the training data is relatively small; 2) Strong reconstruction targets can endow the models with increased capacities on downstream tasks; 3) MIM pre-training is data-agnostic under most scenarios, which means that the strategy of sampling pre-training data is non-critical.

Self-Supervised Learning

VLAB: Enhancing Video Language Pre-training by Feature Adapting and Blending

no code implementations22 May 2023 Xingjian He, Sihan Chen, Fan Ma, Zhicheng Huang, Xiaojie Jin, Zikang Liu, Dongmei Fu, Yi Yang, Jing Liu, Jiashi Feng

Towards this goal, we propose a novel video-text pre-training method dubbed VLAB: Video Language pre-training by feature Adapting and Blending, which transfers CLIP representations to video pre-training tasks and develops unified video multimodal models for a wide range of video-text tasks.

 Ranked #1 on Visual Question Answering (VQA) on MSVD-QA (using extra training data)

Question Answering Retrieval +6

DOAD: Decoupled One Stage Action Detection Network

no code implementations1 Apr 2023 Shuning Chang, Pichao Wang, Fan Wang, Jiashi Feng, Mike Zheng Show

Specifically, one branch focuses on detection representation for actor detection, and the other one for action recognition.

Action Detection Action Recognition +1

OmniAvatar: Geometry-Guided Controllable 3D Head Synthesis

no code implementations CVPR 2023 Hongyi Xu, Guoxian Song, Zihang Jiang, Jianfeng Zhang, Yichun Shi, Jing Liu, WanChun Ma, Jiashi Feng, Linjie Luo

We present OmniAvatar, a novel geometry-guided 3D head synthesis model trained from in-the-wild unstructured images that is capable of synthesizing diverse identity-preserved 3D heads with compelling dynamic details under full disentangled control over camera poses, facial expressions, head shapes, articulated neck and jaw poses.

AgileGAN3D: Few-Shot 3D Portrait Stylization by Augmented Transfer Learning

no code implementations24 Mar 2023 Guoxian Song, Hongyi Xu, Jing Liu, Tiancheng Zhi, Yichun Shi, Jianfeng Zhang, Zihang Jiang, Jiashi Feng, Shen Sang, Linjie Luo

Capitalizing on the recent advancement of 3D-aware GAN models, we perform \emph{guided transfer learning} on a pretrained 3D GAN generator to produce multi-view-consistent stylized renderings.

Transfer Learning

TAPS3D: Text-Guided 3D Textured Shape Generation from Pseudo Supervision

1 code implementation CVPR 2023 Jiacheng Wei, Hao Wang, Jiashi Feng, Guosheng Lin, Kim-Hui Yap

We conduct extensive experiments to analyze each of our proposed components and show the efficacy of our framework in generating high-fidelity 3D textured and text-relevant shapes.

Global Knowledge Calibration for Fast Open-Vocabulary Segmentation

1 code implementation ICCV 2023 Kunyang Han, Yong liu, Jun Hao Liew, Henghui Ding, Yunchao Wei, Jiajun Liu, Yitong Wang, Yansong Tang, Yujiu Yang, Jiashi Feng, Yao Zhao

Recent advancements in pre-trained vision-language models, such as CLIP, have enabled the segmentation of arbitrary concepts solely from textual inputs, a process commonly referred to as open-vocabulary semantic segmentation (OVS).

Knowledge Distillation Open Vocabulary Semantic Segmentation +4

Revisiting Temporal Modeling for CLIP-based Image-to-Video Knowledge Transferring

1 code implementation CVPR 2023 Ruyang Liu, Jingjia Huang, Ge Li, Jiashi Feng, Xinglong Wu, Thomas H. Li

In this paper, based on the CLIP model, we revisit temporal modeling in the context of image-to-video knowledge transferring, which is the key point for extending image-text pretrained models to the video domain.

Ranked #7 on Video Retrieval on MSR-VTT-1kA (using extra training data)

Representation Learning Retrieval +3

MV-Adapter: Multimodal Video Transfer Learning for Video Text Retrieval

1 code implementation19 Jan 2023 Xiaojie Jin, BoWen Zhang, Weibo Gong, Kai Xu, Xueqing Deng, Peng Wang, Zhao Zhang, Xiaohui Shen, Jiashi Feng

The first is a Temporal Adaptation Module that is incorporated in the video branch to introduce global and local temporal contexts.

Retrieval Text Retrieval +2

Temporal Perceiving Video-Language Pre-training

no code implementations18 Jan 2023 Fan Ma, Xiaojie Jin, Heng Wang, Jingjia Huang, Linchao Zhu, Jiashi Feng, Yi Yang

Specifically, text-video localization consists of moment retrieval, which predicts start and end boundaries in videos given the text description, and text localization which matches the subset of texts with the video features.

Contrastive Learning Moment Retrieval +7

CMAE-V: Contrastive Masked Autoencoders for Video Action Recognition

no code implementations15 Jan 2023 Cheng-Ze Lu, Xiaojie Jin, Zhicheng Huang, Qibin Hou, Ming-Ming Cheng, Jiashi Feng

Contrastive Masked Autoencoder (CMAE), as a new self-supervised framework, has shown its potential of learning expressive feature representations in visual image recognition.

Action Recognition Temporal Action Localization

Class Prototype-based Cleaner for Label Noise Learning

1 code implementation21 Dec 2022 Jingjia Huang, Yuanqi Chen, Jiashi Feng, Xinglong Wu

Semi-supervised learning based methods are current SOTA solutions to the noisy-label learning problem, which rely on learning an unsupervised label cleaner first to divide the training samples into a labeled set for clean data and an unlabeled set for noise data.

Ranked #3 on Image Classification on Clothing1M (using extra training data)

Image Classification

PV3D: A 3D Generative Model for Portrait Video Generation

no code implementations13 Dec 2022 Zhongcong Xu, Jianfeng Zhang, Jun Hao Liew, Wenqing Zhang, Song Bai, Jiashi Feng, Mike Zheng Shou

While some prior works have applied such image GANs to unconditional 2D portrait video generation and static 3D portrait synthesis, there are few works successfully extending GANs for generating 3D-aware portrait videos.

Video Generation

Diffusion Probabilistic Model Made Slim

no code implementations CVPR 2023 Xingyi Yang, Daquan Zhou, Jiashi Feng, Xinchao Wang

Despite the recent visually-pleasing results achieved, the massive computational cost has been a long-standing flaw for diffusion probabilistic models (DPMs), which, in turn, greatly limits their applications on resource-limited platforms.

Image Generation Unconditional Image Generation

AvatarGen: A 3D Generative Model for Animatable Human Avatars

1 code implementation26 Nov 2022 Jianfeng Zhang, Zihang Jiang, Dingdong Yang, Hongyi Xu, Yichun Shi, Guoxian Song, Zhongcong Xu, Xinchao Wang, Jiashi Feng

Specifically, we decompose the generative 3D human synthesis into pose-guided mapping and canonical representation with predefined human pose and shape, such that the canonical representation can be explicitly driven to different poses and shapes with the guidance of a 3D parametric human model SMPL.

Expanding Small-Scale Datasets with Guided Imagination

1 code implementation NeurIPS 2023 Yifan Zhang, Daquan Zhou, Bryan Hooi, Kai Wang, Jiashi Feng

Specifically, GIF conducts data imagination by optimizing the latent features of the seed data in the semantically meaningful space of the prior model, resulting in the creation of photo-realistic images with new content.

Conv2Former: A Simple Transformer-Style ConvNet for Visual Recognition

1 code implementation22 Nov 2022 Qibin Hou, Cheng-Ze Lu, Ming-Ming Cheng, Jiashi Feng

This paper does not attempt to design a state-of-the-art method for visual recognition but investigates a more efficient way to make use of convolutions to encode spatial features.

object-detection Object Detection +1

MagicVideo: Efficient Video Generation With Latent Diffusion Models

no code implementations20 Nov 2022 Daquan Zhou, Weimin WANG, Hanshu Yan, Weiwei Lv, Yizhe Zhu, Jiashi Feng

In specific, unlike existing works that directly train video models in the RGB space, we use a pre-trained VAE to map video clips into a low-dimensional latent space and learn the distribution of videos' latent codes via a diffusion model.

Text-to-Video Generation Video Generation

MagicMix: Semantic Mixing with Diffusion Models

2 code implementations28 Oct 2022 Jun Hao Liew, Hanshu Yan, Daquan Zhou, Jiashi Feng

Unlike style transfer, where an image is stylized according to the reference style without changing the image content, semantic blending mixes two different concepts in a semantic manner to synthesize a novel concept while preserving the spatial layout and geometry.

Denoising Style Transfer

MetaFormer Baselines for Vision

7 code implementations24 Oct 2022 Weihao Yu, Chenyang Si, Pan Zhou, Mi Luo, Yichen Zhou, Jiashi Feng, Shuicheng Yan, Xinchao Wang

By simply applying depthwise separable convolutions as token mixer in the bottom stages and vanilla self-attention in the top stages, the resulting model CAFormer sets a new record on ImageNet-1K: it achieves an accuracy of 85. 5% at 224x224 resolution, under normal supervised training without external data or distillation.

Ranked #2 on Domain Generalization on ImageNet-C (using extra training data)

Domain Generalization Image Classification

Reachability-Aware Laplacian Representation in Reinforcement Learning

no code implementations24 Oct 2022 Kaixin Wang, Kuangqi Zhou, Jiashi Feng, Bryan Hooi, Xinchao Wang

In Reinforcement Learning (RL), Laplacian Representation (LapRep) is a task-agnostic state representation that encodes the geometry of the environment.

reinforcement-learning Reinforcement Learning (RL)

Scaling & Shifting Your Features: A New Baseline for Efficient Model Tuning

1 code implementation17 Oct 2022 Dongze Lian, Daquan Zhou, Jiashi Feng, Xinchao Wang

With the proposed SSF, our model obtains 2. 46% (90. 72% vs. 88. 54%) and 11. 48% (73. 10% vs. 65. 57%) performance improvement on FGVC and VTAB-1k in terms of Top-1 accuracy compared to the full fine-tuning but only fine-tuning about 0. 3M parameters.

Image Classification

ManiCLIP: Multi-Attribute Face Manipulation from Text

1 code implementation2 Oct 2022 Hao Wang, Guosheng Lin, Ana García del Molino, Anran Wang, Jiashi Feng, Zhiqi Shen

In this paper we present a novel multi-attribute face manipulation method based on textual descriptions.

Attribute Text-based Image Editing

AvatarGen: a 3D Generative Model for Animatable Human Avatars

1 code implementation1 Aug 2022 Jianfeng Zhang, Zihang Jiang, Dingdong Yang, Hongyi Xu, Yichun Shi, Guoxian Song, Zhongcong Xu, Xinchao Wang, Jiashi Feng

Unsupervised generation of clothed virtual humans with various appearance and animatable poses is important for creating 3D human avatars and other AR/VR applications.

3D Human Reconstruction

Contrastive Masked Autoencoders are Stronger Vision Learners

1 code implementation27 Jul 2022 Zhicheng Huang, Xiaojie Jin, Chengze Lu, Qibin Hou, Ming-Ming Cheng, Dongmei Fu, Xiaohui Shen, Jiashi Feng

The momentum encoder, fed with the full images, enhances the feature discriminability via contrastive learning with its online counterpart.

Contrastive Learning Decoder +4

Clover: Towards A Unified Video-Language Alignment and Fusion Model

1 code implementation CVPR 2023 Jingjia Huang, Yinan Li, Jiashi Feng, Xinglong Wu, Xiaoshuai Sun, Rongrong Ji

We then introduce \textbf{Clover}\textemdash a Correlated Video-Language pre-training method\textemdash towards a universal Video-Language model for solving multiple video understanding tasks with neither performance nor efficiency compromise.

Language Modelling Question Answering +10

Divide to Adapt: Mitigating Confirmation Bias for Domain Adaptation of Black-Box Predictors

1 code implementation28 May 2022 Jianfei Yang, Xiangyu Peng, Kai Wang, Zheng Zhu, Jiashi Feng, Lihua Xie, Yang You

Domain Adaptation of Black-box Predictors (DABP) aims to learn a model on an unlabeled target domain supervised by a black-box predictor trained on a source domain.

Domain Adaptation Knowledge Distillation

Sharpness-Aware Training for Free

1 code implementation27 May 2022 Jiawei Du, Daquan Zhou, Jiashi Feng, Vincent Y. F. Tan, Joey Tianyi Zhou

Intuitively, SAF achieves this by avoiding sudden drops in the loss in the sharp local minima throughout the trajectory of the updates of the weights.

Tyger: Task-Type-Generic Active Learning for Molecular Property Prediction

no code implementations23 May 2022 Kuangqi Zhou, Kaixin Wang, Jiashi Feng, Jian Tang, Tingyang Xu, Xinchao Wang

However, existing best deep AL methods are mostly developed for a single type of learning task (e. g., single-label classification), and hence may not perform well in molecular property prediction that involves various task types.

Active Learning Drug Discovery +3

Understanding The Robustness in Vision Transformers

2 code implementations26 Apr 2022 Daquan Zhou, Zhiding Yu, Enze Xie, Chaowei Xiao, Anima Anandkumar, Jiashi Feng, Jose M. Alvarez

Our study is motivated by the intriguing properties of the emerging visual grouping in Vision Transformers, which indicates that self-attention may promote robustness through improved mid-level representations.

Ranked #4 on Domain Generalization on ImageNet-R (using extra training data)

Domain Generalization Image Classification +3

Generalizing Few-Shot NAS with Gradient Matching

1 code implementation ICLR 2022 Shoukang Hu, Ruochen Wang, Lanqing Hong, Zhenguo Li, Cho-Jui Hsieh, Jiashi Feng

Efficient performance estimation of architectures drawn from large search spaces is essential to Neural Architecture Search.

Neural Architecture Search

PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination under Self-supervision

1 code implementation CVPR 2022 Kehong Gong, Bingbing Li, Jianfeng Zhang, Tao Wang, Jing Huang, Michael Bi Mi, Jiashi Feng, Xinchao Wang

Existing self-supervised 3D human pose estimation schemes have largely relied on weak supervisions like consistency loss to guide the learning, which, inevitably, leads to inferior results in real-world scenarios with unseen poses.

3D Human Pose Estimation Hallucination

SODAR: Segmenting Objects by DynamicallyAggregating Neighboring Mask Representations

1 code implementation15 Feb 2022 Tao Wang, Jun Hao Liew, Yu Li, Yunpeng Chen, Jiashi Feng

Unlike the original per grid cell object masks, SODAR is implicitly supervised to learn mask representations that encode geometric structure of nearby objects and complement adjacent representations with context.

Instance Segmentation Object +1

The Geometry of Robust Value Functions

no code implementations30 Jan 2022 Kaixin Wang, Navdeep Kumar, Kuangqi Zhou, Bryan Hooi, Jiashi Feng, Shie Mannor

The key of this perspective is to decompose the value space, in a state-wise manner, into unions of hypersurfaces.

Towards Adversarially Robust Deep Image Denoising

no code implementations12 Jan 2022 Hanshu Yan, Jingfeng Zhang, Jiashi Feng, Masashi Sugiyama, Vincent Y. F. Tan

Secondly, to robustify DIDs, we propose an adversarial training strategy, hybrid adversarial training ({\sc HAT}), that jointly trains DIDs with adversarial and non-adversarial noisy data to ensure that the reconstruction quality is high and the denoisers around non-adversarial data are locally smooth.

Adversarial Attack Adversarial Robustness +1

UMAD: Universal Model Adaptation under Domain and Category Shift

no code implementations16 Dec 2021 Jian Liang, Dapeng Hu, Jiashi Feng, Ran He

To achieve bilateral adaptation in the target domain, we further maximize localized mutual information to align known samples with the source classifier and employ an entropic loss to push unknown samples far away from the source classification boundary, respectively.

Universal Domain Adaptation Unsupervised Domain Adaptation

Mimicking the Oracle: An Initial Phase Decorrelation Approach for Class Incremental Learning

1 code implementation CVPR 2022 Yujun Shi, Kuangqi Zhou, Jian Liang, Zihang Jiang, Jiashi Feng, Philip Torr, Song Bai, Vincent Y. F. Tan

Specifically, we experimentally show that directly encouraging CIL Learner at the initial phase to output similar representations as the model jointly trained on all classes can greatly boost the CIL performance.

Class Incremental Learning Incremental Learning

Geometry-Guided Progressive NeRF for Generalizable and Efficient Neural Human Rendering

no code implementations8 Dec 2021 Mingfei Chen, Jianfeng Zhang, Xiangyu Xu, Lijuan Liu, Yujun Cai, Jiashi Feng, Shuicheng Yan

Meanwhile, for achieving higher rendering efficiency, we introduce a progressive rendering pipeline through geometry guidance, which leverages the geometric feature volume and the predicted density values to progressively reduce the number of sampling points and speed up the rendering process.

Towards Understanding Why Lookahead Generalizes Better Than SGD and Beyond

1 code implementation NeurIPS 2021 Pan Zhou, Hanshu Yan, Xiaotong Yuan, Jiashi Feng, Shuicheng Yan

Specifically, we prove that lookahead using SGD as its inner-loop optimizer can better balance the optimization error and generalization error to achieve smaller excess risk error than vanilla SGD on (strongly) convex problems and nonconvex problems with Polyak-{\L}ojasiewicz condition which has been observed/proved in neural networks.

Shunted Self-Attention via Multi-Scale Token Aggregation

1 code implementation CVPR 2022 Sucheng Ren, Daquan Zhou, Shengfeng He, Jiashi Feng, Xinchao Wang

This novel merging scheme enables the self-attention to learn relationships between objects with different sizes and simultaneously reduces the token numbers and the computational cost.

MetaFormer Is Actually What You Need for Vision

14 code implementations CVPR 2022 Weihao Yu, Mi Luo, Pan Zhou, Chenyang Si, Yichen Zhou, Xinchao Wang, Jiashi Feng, Shuicheng Yan

Based on this observation, we hypothesize that the general architecture of the Transformers, instead of the specific token mixer module, is more essential to the model's performance.

Image Classification Object Detection +1

Direct Multi-view Multi-person 3D Pose Estimation

2 code implementations NeurIPS 2021 Tao Wang, Jianfeng Zhang, Yujun Cai, Shuicheng Yan, Jiashi Feng

Instead of estimating 3D joint locations from costly volumetric representation or reconstructing the per-person 3D pose from multiple detected 2D poses as in previous methods, MvP directly regresses the multi-person 3D poses in a clean and efficient way, without relying on intermediate tasks.

Ranked #3 on 3D Multi-Person Pose Estimation on Panoptic (using extra training data)

3D Multi-Person Pose Estimation 3D Pose Estimation

Deep Long-Tailed Learning: A Survey

1 code implementation9 Oct 2021 Yifan Zhang, Bingyi Kang, Bryan Hooi, Shuicheng Yan, Jiashi Feng

Deep long-tailed learning, one of the most challenging problems in visual recognition, aims to train well-performing deep models from a large number of images that follow a long-tailed class distribution.

Efficient Sharpness-aware Minimization for Improved Training of Neural Networks

1 code implementation ICLR 2022 Jiawei Du, Hanshu Yan, Jiashi Feng, Joey Tianyi Zhou, Liangli Zhen, Rick Siow Mong Goh, Vincent Y. F. Tan

Recently, the relation between the sharpness of the loss landscape and the generalization error has been established by Foret et al. (2020), in which the Sharpness Aware Minimizer (SAM) was proposed to mitigate the degradation of the generalization.

How Well Does Self-Supervised Pre-Training Perform with Streaming ImageNet?

no code implementations NeurIPS Workshop ImageNet_PPF 2021 Dapeng Hu, Shipeng Yan, Qizhengqiu Lu, Lanqing Hong, Hailin Hu, Yifan Zhang, Zhenguo Li, Xinchao Wang, Jiashi Feng

Prior works on self-supervised pre-training focus on the joint training scenario, where massive unlabeled data are assumed to be given as input all at once, and only then is a learner trained.

Self-Supervised Learning

PnP-DETR: Towards Efficient Visual Analysis with Transformers

1 code implementation ICCV 2021 Tao Wang, Li Yuan, Yunpeng Chen, Jiashi Feng, Shuicheng Yan

Recently, DETR pioneered the solution of vision tasks with transformers, it directly translates the image feature map into the object detection result.

object-detection Object Detection +1

Voxel Transformer for 3D Object Detection

1 code implementation ICCV 2021 Jiageng Mao, Yujing Xue, Minzhe Niu, Haoyue Bai, Jiashi Feng, Xiaodan Liang, Hang Xu, Chunjing Xu

We present Voxel Transformer (VoTr), a novel and effective voxel-based Transformer backbone for 3D object detection from point clouds.

Ranked #3 on 3D Object Detection on waymo vehicle (L1 mAP metric)

3D Object Detection Computational Efficiency +3

Triplet Contrastive Learning for Brain Tumor Classification

no code implementations8 Aug 2021 Tian Yu Liu, Jiashi Feng

Brain tumor is a common and fatal form of cancer which affects both adults and children.

Classification Contrastive Learning +2

Self-Supervised Aggregation of Diverse Experts for Test-Agnostic Long-Tailed Recognition

2 code implementations20 Jul 2021 Yifan Zhang, Bryan Hooi, Lanqing Hong, Jiashi Feng

Existing long-tailed recognition methods, aiming to train class-balanced models from long-tailed data, generally assume the models would be evaluated on the uniform test class distribution.

Image Classification Long-tail Learning

Recovering the Unbiased Scene Graphs from the Biased Ones

1 code implementation5 Jul 2021 Meng-Jiun Chiou, Henghui Ding, Hanshu Yan, Changhu Wang, Roger Zimmermann, Jiashi Feng

Given input images, scene graph generation (SGG) aims to produce comprehensive, graphical representations describing visual relationships among salient objects.

Missing Labels Scene Graph Classification +4

VOLO: Vision Outlooker for Visual Recognition

7 code implementations24 Jun 2021 Li Yuan, Qibin Hou, Zihang Jiang, Jiashi Feng, Shuicheng Yan

Though recently the prevailing vision transformers (ViTs) have shown great potential of self-attention based models in ImageNet classification, their performance is still inferior to that of the latest SOTA CNNs if no extra data are provided.

Domain Generalization Image Classification +1

Vision Permutator: A Permutable MLP-Like Architecture for Visual Recognition

4 code implementations23 Jun 2021 Qibin Hou, Zihang Jiang, Li Yuan, Ming-Ming Cheng, Shuicheng Yan, Jiashi Feng

By realizing the importance of the positional information carried by 2D feature representations, unlike recent MLP-like models that encode the spatial information along the flattened spatial dimensions, Vision Permutator separately encodes the feature representations along the height and width dimensions with linear projections.

LV-BERT: Exploiting Layer Variety for BERT

1 code implementation Findings (ACL) 2021 Weihao Yu, Zihang Jiang, Fei Chen, Qibin Hou, Jiashi Feng

In this paper, beyond this stereotyped layer pattern, we aim to improve pre-trained models by exploiting layer variety from two aspects: the layer type set and the layer order.

No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data

1 code implementation NeurIPS 2021 Mi Luo, Fei Chen, Dapeng Hu, Yifan Zhang, Jian Liang, Jiashi Feng

Motivated by the above findings, we propose a novel and simple algorithm called Classifier Calibration with Virtual Representations (CCVR), which adjusts the classifier using virtual representations sampled from an approximated gaussian mixture model.

Classifier calibration Federated Learning

Refiner: Refining Self-attention for Vision Transformers

1 code implementation7 Jun 2021 Daquan Zhou, Yujun Shi, Bingyi Kang, Weihao Yu, Zihang Jiang, Yuan Li, Xiaojie Jin, Qibin Hou, Jiashi Feng

Vision Transformers (ViTs) have shown competitive accuracy in image classification tasks compared with CNNs.

Image Classification

Image-to-Video Generation via 3D Facial Dynamics

no code implementations31 May 2021 Xiaoguang Tu, Yingtian Zou, Jian Zhao, Wenjie Ai, Jian Dong, Yuan YAO, Zhikang Wang, Guodong Guo, Zhifeng Li, Wei Liu, Jiashi Feng

Video generation from a single face image is an interesting problem and usually tackled by utilizing Generative Adversarial Networks (GANs) to integrate information from the input face image and a sequence of sparse facial landmarks.

Image to Video Generation Video Prediction

PSGAN++: Robust Detail-Preserving Makeup Transfer and Removal

1 code implementation26 May 2021 Si Liu, Wentao Jiang, Chen Gao, Ran He, Jiashi Feng, Bo Li, Shuicheng Yan

In this paper, we address the makeup transfer and removal tasks simultaneously, which aim to transfer the makeup from a reference image to a source image and remove the makeup from the with-makeup image respectively.

Style Transfer

Joint Face Image Restoration and Frontalization for Recognition

no code implementations12 May 2021 Xiaoguang Tu, Jian Zhao, Qiankun Liu, Wenjie Ai, Guodong Guo, Zhifeng Li, Wei Liu, Jiashi Feng

First, MDFR is a well-designed encoder-decoder architecture which extracts feature representation from an input face image with arbitrary low-quality factors and restores it to a high-quality counterpart.

Decoder Face Recognition +1

Body Meshes as Points

1 code implementation CVPR 2021 Jianfeng Zhang, Dongdong Yu, Jun Hao Liew, Xuecheng Nie, Jiashi Feng

In this work, we present a single-stage model, Body Meshes as Points (BMP), to simplify the pipeline and lift both efficiency and performance.

3D Human Shape Estimation 3D Multi-Person Pose Estimation +1

PoseAug: A Differentiable Pose Augmentation Framework for 3D Human Pose Estimation

1 code implementation CVPR 2021 Kehong Gong, Jianfeng Zhang, Jiashi Feng

To address this problem, we present PoseAug, a new auto-augmentation framework that learns to augment the available training poses towards a greater diversity and thus improve generalization of the trained 2D-to-3D pose estimator.

 Ranked #1 on Monocular 3D Human Pose Estimation on Human3.6M (Use Video Sequence metric)

Data Augmentation Monocular 3D Human Pose Estimation +1

How Well Does Self-Supervised Pre-Training Perform with Streaming Data?

no code implementations ICLR 2022 Dapeng Hu, Shipeng Yan, Qizhengqiu Lu, Lanqing Hong, Hailin Hu, Yifan Zhang, Zhenguo Li, Xinchao Wang, Jiashi Feng

Prior works on self-supervised pre-training focus on the joint training scenario, where massive unlabeled data are assumed to be given as input all at once, and only then is a learner trained.

Representation Learning Self-Supervised Learning

DINE: Domain Adaptation from Single and Multiple Black-box Predictors

3 code implementations CVPR 2022 Jian Liang, Dapeng Hu, Jiashi Feng, Ran He

To ease the burden of labeling, unsupervised domain adaptation (UDA) aims to transfer knowledge in previous and related labeled datasets (sources) to a new unlabeled dataset (target).

Transductive Learning Unsupervised Domain Adaptation

Augmented Transformer with Adaptive Graph for Temporal Action Proposal Generation

no code implementations30 Mar 2021 Shuning Chang, Pichao Wang, Fan Wang, Hao Li, Jiashi Feng

Temporal action proposal generation (TAPG) is a fundamental and challenging task in video understanding, especially in temporal action detection.

Action Detection Temporal Action Proposal Generation +1

AutoSpace: Neural Architecture Search with Less Human Interference

1 code implementation ICCV 2021 Daquan Zhou, Xiaojie Jin, Xiaochen Lian, Linjie Yang, Yujing Xue, Qibin Hou, Jiashi Feng

Current neural architecture search (NAS) algorithms still require expert knowledge and effort to design a search space for network construction.

Neural Architecture Search

DeepViT: Towards Deeper Vision Transformer

5 code implementations22 Mar 2021 Daquan Zhou, Bingyi Kang, Xiaojie Jin, Linjie Yang, Xiaochen Lian, Zihang Jiang, Qibin Hou, Jiashi Feng

In this paper, we show that, unlike convolution neural networks (CNNs)that can be improved by stacking more convolutional layers, the performance of ViTs saturate fast when scaled to be deeper.

Image Classification Representation Learning

Coordinate Attention for Efficient Mobile Network Design

2 code implementations CVPR 2021 Qibin Hou, Daquan Zhou, Jiashi Feng

Recent studies on mobile network design have demonstrated the remarkable effectiveness of channel attention (e. g., the Squeeze-and-Excitation attention) for lifting model performance, but they generally neglect the positional information, which is important for generating spatially selective attention maps.

object-detection Object Detection +1

Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning

1 code implementation NeurIPS 2021 Yifan Zhang, Bryan Hooi, Dapeng Hu, Jian Liang, Jiashi Feng

In this paper, we investigate whether applying contrastive learning to fine-tuning would bring further benefits, and analytically find that optimizing the contrastive loss benefits both discriminative representation learning and model optimization during fine-tuning.

Contrastive Learning Image Classification +4

CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection

2 code implementations10 Feb 2021 Hanshu Yan, Jingfeng Zhang, Gang Niu, Jiashi Feng, Vincent Y. F. Tan, Masashi Sugiyama

By comparing \textit{non-robust} (normally trained) and \textit{robustified} (adversarially trained) models, we observe that adversarial training (AT) robustifies CNNs by aligning the channel-wise activations of adversarial data with those of their natural counterparts.

Adversarial Robustness feature selection

Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet

13 code implementations ICCV 2021 Li Yuan, Yunpeng Chen, Tao Wang, Weihao Yu, Yujun Shi, Zihang Jiang, Francis EH Tay, Jiashi Feng, Shuicheng Yan

To overcome such limitations, we propose a new Tokens-To-Token Vision Transformer (T2T-ViT), which incorporates 1) a layer-wise Tokens-to-Token (T2T) transformation to progressively structurize the image to tokens by recursively aggregating neighboring Tokens into one Token (Tokens-to-Token), such that local structure represented by surrounding tokens can be modeled and tokens length can be reduced; 2) an efficient backbone with a deep-narrow structure for vision transformer motivated by CNN architecture design after empirical study.

Image Classification Language Modelling

ORDNet: Capturing Omni-Range Dependencies for Scene Parsing

no code implementations11 Jan 2021 Shaofei Huang, Si Liu, Tianrui Hui, Jizhong Han, Bo Li, Jiashi Feng, Shuicheng Yan

Our ORDNet is able to extract more comprehensive context information and well adapt to complex spatial variance in scene images.

Scene Parsing

Exploring Balanced Feature Spaces for Representation Learning

no code implementations ICLR 2021 Bingyi Kang, Yu Li, Sa Xie, Zehuan Yuan, Jiashi Feng

Motivated by this question, we conduct a series of studies on the performance of self-supervised contrastive learning and supervised learning methods over multiple datasets where training instance distributions vary from a balanced one to a long-tailed one.

Contrastive Learning Long-tail Learning +2

AggMask: Exploring locally aggregated learning of mask representations for instance segmentation

1 code implementation1 Jan 2021 Tao Wang, Jun Hao Liew, Yu Li, Yunpeng Chen, Jiashi Feng

Recently proposed one-stage instance segmentation models (\emph{e. g.}, SOLO) learn to directly predict location-specific object mask with fully-convolutional networks.

Instance Segmentation Segmentation +1

DiffAutoML: Differentiable Joint Optimization for Efficient End-to-End Automated Machine Learning

no code implementations1 Jan 2021 Kaichen Zhou, Lanqing Hong, Fengwei Zhou, Binxin Ru, Zhenguo Li, Trigoni Niki, Jiashi Feng

Our method performs co-optimization of the neural architectures, training hyper-parameters and data augmentation policies in an end-to-end fashion without the need of model retraining.

BIG-bench Machine Learning Computational Efficiency +2

Learning Safe Policies with Cost-sensitive Advantage Estimation

no code implementations1 Jan 2021 Bingyi Kang, Shie Mannor, Jiashi Feng

Reinforcement Learning (RL) with safety guarantee is critical for agents performing tasks in risky environments.

Reinforcement Learning (RL)

Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer

2 code implementations14 Dec 2020 Jian Liang, Dapeng Hu, Yunbo Wang, Ran He, Jiashi Feng

Furthermore, we propose a new labeling transfer strategy, which separates the target data into two splits based on the confidence of predictions (labeling information), and then employ semi-supervised learning to improve the accuracy of less-confident predictions in the target domain.

Classification General Classification +4

Residual Distillation: Towards Portable Deep Neural Networks without Shortcuts

1 code implementation NeurIPS 2020 Guilin Li, Junlei Zhang, Yunhe Wang, Chuanjian Liu, Matthias Tan, Yunfeng Lin, Wei zhang, Jiashi Feng, Tong Zhang

In particular, we propose a novel joint-training framework to train plain CNN by leveraging the gradients of the ResNet counterpart.

Fooling the primate brain with minimal, targeted image manipulation

no code implementations11 Nov 2020 Li Yuan, Will Xiao, Giorgia Dellaferrera, Gabriel Kreiman, Francis E. H. Tay, Jiashi Feng, Margaret S. Livingstone

Here we propose an array of methods for creating minimal, targeted image perturbations that lead to changes in both neuronal activity and perception as reflected in behavior.

Adversarial Attack Image Manipulation

Improving Generalization in Reinforcement Learning with Mixture Regularization

2 code implementations NeurIPS 2020 Kaixin Wang, Bingyi Kang, Jie Shao, Jiashi Feng

Deep reinforcement learning (RL) agents trained in a limited set of environments tend to suffer overfitting and fail to generalize to unseen testing environments.

Data Augmentation reinforcement-learning +1

Toward Accurate Person-level Action Recognition in Videos of Crowded Scenes

no code implementations16 Oct 2020 Li Yuan, Yichen Zhou, Shuning Chang, Ziyuan Huang, Yunpeng Chen, Xuecheng Nie, Tao Wang, Jiashi Feng, Shuicheng Yan

Prior works always fail to deal with this problem in two aspects: (1) lacking utilizing information of the scenes; (2) lacking training data in the crowd and complex scenes.

Action Recognition In Videos Semantic Segmentation

A Simple Baseline for Pose Tracking in Videos of Crowded Scenes

no code implementations16 Oct 2020 Li Yuan, Shuning Chang, Ziyuan Huang, Yichen Zhou, Yunpeng Chen, Xuecheng Nie, Francis E. H. Tay, Jiashi Feng, Shuicheng Yan

This paper presents our solution to ACM MM challenge: Large-scale Human-centric Video Analysis in Complex Events\cite{lin2020human}; specifically, here we focus on Track3: Crowd Pose Tracking in Complex Events.

Multi-Object Tracking Optical Flow Estimation +1

Towards Accurate Human Pose Estimation in Videos of Crowded Scenes

no code implementations16 Oct 2020 Li Yuan, Shuning Chang, Xuecheng Nie, Ziyuan Huang, Yichen Zhou, Yunpeng Chen, Jiashi Feng, Shuicheng Yan

In this paper, we focus on improving human pose estimation in videos of crowded scenes from the perspectives of exploiting temporal context and collecting new data.

Optical Flow Estimation Pose Estimation

Towards Theoretically Understanding Why SGD Generalizes Better Than ADAM in Deep Learning

no code implementations NeurIPS 2020 Pan Zhou, Jiashi Feng, Chao Ma, Caiming Xiong, Steven Hoi, Weinan E

The result shows that (1) the escaping time of both SGD and ADAM~depends on the Radon measure of the basin positively and the heaviness of gradient noise negatively; (2) for the same basin, SGD enjoys smaller escaping time than ADAM, mainly because (a) the geometry adaptation in ADAM~via adaptively scaling each gradient coordinate well diminishes the anisotropic structure in gradient noise and results in larger Radon measure of a basin; (b) the exponential gradient average in ADAM~smooths its gradient and leads to lighter gradient noise tails than SGD.

Visual Relationship Detection with Visual-Linguistic Knowledge from Multimodal Representations

1 code implementation10 Sep 2020 Meng-Jiun Chiou, Roger Zimmermann, Jiashi Feng

Visual relationship detection aims to reason over relationships among salient objects in images, which has drawn increasing attention over the past few years.

Object object-detection +4

Dual Adversarial Auto-Encoders for Clustering

no code implementations23 Aug 2020 Pengfei Ge, Chuan-Xian Ren, Jiashi Feng, Shuicheng Yan

By performing variational inference on the objective function of Dual-AAE, we derive a new reconstruction loss which can be optimized by training a pair of Auto-encoders.

Clustering Variational Inference

ConvBERT: Improving BERT with Span-based Dynamic Convolution

7 code implementations NeurIPS 2020 Zi-Hang Jiang, Weihao Yu, Daquan Zhou, Yunpeng Chen, Jiashi Feng, Shuicheng Yan

The novel convolution heads, together with the rest self-attention heads, form a new mixed attention block that is more efficient at both global and local context learning.

Natural Language Understanding

Few-shot Classification via Adaptive Attention

1 code implementation6 Aug 2020 Zi-Hang Jiang, Bingyi Kang, Kuangqi Zhou, Jiashi Feng

To be specific, we devise a simple and efficient meta-reweighting strategy to adapt the sample representations and generate soft attention to refine the representation such that the relevant features from the query and support samples can be extracted for a better few-shot classification.

Classification Few-Shot Learning +1

The Devil is in Classification: A Simple Framework for Long-tail Object Detection and Instance Segmentation

1 code implementation ECCV 2020 Tao Wang, Yu Li, Bingyi Kang, Junnan Li, Junhao Liew, Sheng Tang, Steven Hoi, Jiashi Feng

Specifically, we systematically investigate performance drop of the state-of-the-art two-stage instance segmentation model Mask R-CNN on the recent long-tail LVIS dataset, and unveil that a major cause is the inaccurate classification of object proposals.

General Classification Instance Segmentation +4

Domain Adaptation with Auxiliary Target Domain-Oriented Classifier

2 code implementations CVPR 2021 Jian Liang, Dapeng Hu, Jiashi Feng

ATDOC alleviates the classifier bias by introducing an auxiliary classifier for target data only, to improve the quality of pseudo labels.

Domain Adaptation Transfer Learning

Rethinking Bottleneck Structure for Efficient Mobile Network Design

4 code implementations ECCV 2020 Zhou Daquan, Qibin Hou, Yunpeng Chen, Jiashi Feng, Shuicheng Yan

In this paper, we rethink the necessity of such design changes and find it may bring risks of information loss and gradient confusion.

General Classification Neural Architecture Search +2

Local Grid Rendering Networks for 3D Object Detection in Point Clouds

no code implementations4 Jul 2020 Jianan Li, Jiashi Feng

The performance of 3D object detection models over point clouds highly depends on their capability of modeling local geometric patterns.

3D Object Detection Computational Efficiency +1

Inference Stage Optimization for Cross-scenario 3D Human Pose Estimation

no code implementations NeurIPS 2020 Jianfeng Zhang, Xuecheng Nie, Jiashi Feng

In this work, we propose a novel framework, Inference Stage Optimization (ISO), for improving the generalizability of 3D pose models when source and target data come from different pose distributions.

Ranked #118 on 3D Human Pose Estimation on 3DPW (PA-MPJPE metric)

3D Human Pose Estimation Self-Supervised Learning

Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax

2 code implementations CVPR 2020 Yu Li, Tao Wang, Bingyi Kang, Sheng Tang, Chunfeng Wang, Jintao Li, Jiashi Feng

Solving long-tail large vocabulary object detection with deep learning based models is a challenging and demanding task, which is however under-explored. In this work, we provide the first systematic analysis on the underperformance of state-of-the-art models in front of long-tail distribution.

Image Classification Instance Segmentation +5

Multi-Miner: Object-Adaptive Region Mining for Weakly-Supervised Semantic Segmentation

no code implementations14 Jun 2020 Kuangqi Zhou, Qibin Hou, Zun Li, Jiashi Feng

In this paper, we propose a novel multi-miner framework to perform a region mining process that adapts to diverse object sizes and is thus able to mine more integral and finer object regions.

Object Segmentation +2

Understanding and Resolving Performance Degradation in Graph Convolutional Networks

2 code implementations12 Jun 2020 Kuangqi Zhou, Yanfei Dong, Kaixin Wang, Wee Sun Lee, Bryan Hooi, Huan Xu, Jiashi Feng

In this work, we study performance degradation of GCNs by experimentally examining how stacking only TRANs or PROPs works.

Boosting Few-Shot Learning With Adaptive Margin Loss

no code implementations CVPR 2020 Aoxue Li, Weiran Huang, Xu Lan, Jiashi Feng, Zhenguo Li, Li-Wei Wang

Few-shot learning (FSL) has attracted increasing attention in recent years but remains challenging, due to the intrinsic difficulty in learning to generalize from a few examples.

Few-Shot Image Classification Few-Shot Learning +2

Semantic Domain Adversarial Networks for Unsupervised Domain Adaptation

no code implementations30 Mar 2020 Dapeng Hu, Jian Liang, Qibin Hou, Hanshu Yan, Yunpeng Chen, Shuicheng Yan, Jiashi Feng

To successfully align the multi-modal data structures across domains, the following works exploit discriminative information in the adversarial training process, e. g., using multiple class-wise discriminators and introducing conditional information in input or output of the domain discriminator.

Object Recognition Semantic Segmentation +1

Strip Pooling: Rethinking Spatial Pooling for Scene Parsing

2 code implementations CVPR 2020 Qibin Hou, Li Zhang, Ming-Ming Cheng, Jiashi Feng

Spatial pooling has been proven highly effective in capturing long-range contextual information for pixel-wise prediction tasks, such as scene parsing.

Scene Parsing Semantic Segmentation

Cross-layer Feature Pyramid Network for Salient Object Detection

no code implementations25 Feb 2020 Zun Li, Congyan Lang, Junhao Liew, Qibin Hou, Yidong Li, Jiashi Feng

Feature pyramid network (FPN) based models, which fuse the semantics and salient details in a progressive manner, have been proven highly effective in salient object detection.

Object object-detection +2

ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning

1 code implementation ICLR 2020 Weihao Yu, Zi-Hang Jiang, Yanfei Dong, Jiashi Feng

Empirical results show that state-of-the-art models have an outstanding ability to capture biases contained in the dataset with high accuracy on EASY set.

Logical Reasoning Logical Reasoning Question Answering +2

The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up

4 code implementations9 Feb 2020 Razvan V. Marinescu, Neil P. Oxtoby, Alexandra L. Young, Esther E. Bron, Arthur W. Toga, Michael W. Weiner, Frederik Barkhof, Nick C. Fox, Arman Eshaghi, Tina Toni, Marcin Salaterski, Veronika Lunina, Manon Ansart, Stanley Durrleman, Pascal Lu, Samuel Iddi, Dan Li, Wesley K. Thompson, Michael C. Donohue, Aviv Nahon, Yarden Levy, Dan Halbersberg, Mariya Cohen, Huiling Liao, Tengfei Li, Kaixian Yu, Hongtu Zhu, Jose G. Tamez-Pena, Aya Ismail, Timothy Wood, Hector Corrada Bravo, Minh Nguyen, Nanbo Sun, Jiashi Feng, B. T. Thomas Yeo, Gang Chen, Ke Qi, Shiyang Chen, Deqiang Qiu, Ionut Buciuman, Alex Kelner, Raluca Pop, Denisa Rimocea, Mostafa M. Ghazi, Mads Nielsen, Sebastien Ourselin, Lauge Sorensen, Vikram Venkatraghavan, Keli Liu, Christina Rabe, Paul Manser, Steven M. Hill, James Howlett, Zhiyue Huang, Steven Kiddle, Sach Mukherjee, Anais Rouanet, Bernd Taschler, Brian D. M. Tom, Simon R. White, Noel Faux, Suman Sedai, Javier de Velasco Oriol, Edgar E. V. Clemente, Karol Estrada, Leon Aksman, Andre Altmann, Cynthia M. Stonnington, Yalin Wang, Jianfeng Wu, Vivek Devadas, Clementine Fourrier, Lars Lau Raket, Aristeidis Sotiras, Guray Erus, Jimit Doshi, Christos Davatzikos, Jacob Vogel, Andrew Doyle, Angela Tam, Alex Diaz-Papkovich, Emmanuel Jammeh, Igor Koval, Paul Moore, Terry J. Lyons, John Gallacher, Jussi Tohka, Robert Ciszek, Bruno Jedynak, Kruti Pandya, Murat Bilgel, William Engels, Joseph Cole, Polina Golland, Stefan Klein, Daniel C. Alexander

TADPOLE's unique results suggest that current prediction algorithms provide sufficient accuracy to exploit biomarkers related to clinical diagnosis and ventricle volume, for cohort refinement in clinical trials for Alzheimer's disease.

Alzheimer's Disease Detection Disease Prediction

MetaSelector: Meta-Learning for Recommendation with User-Level Adaptive Model Selection

no code implementations22 Jan 2020 Mi Luo, Fei Chen, Pengxiang Cheng, Zhenhua Dong, Xiuqiang He, Jiashi Feng, Zhenguo Li

Recommender systems often face heterogeneous datasets containing highly personalized historical data of users, where no single model could give the best recommendation for every user.

Meta-Learning Model Selection +1

RC-DARTS: Resource Constrained Differentiable Architecture Search

no code implementations30 Dec 2019 Xiaojie Jin, Jiang Wang, Joshua Slocum, Ming-Hsuan Yang, Shengyang Dai, Shuicheng Yan, Jiashi Feng

In this paper, we propose the resource constrained differentiable architecture search (RC-DARTS) method to learn architectures that are significantly smaller and faster while achieving comparable accuracy.

Image Classification One-Shot Learning

Zoom in to where it matters: a hierarchical graph based model for mammogram analysis

no code implementations16 Dec 2019 Hao Du, Jiashi Feng, Mengling Feng

In clinical practice, human radiologists actually review medical images with high resolution monitors and zoom into region of interests (ROIs) for a close-up examination.

General Classification Graph Attention +2

Efficient Meta Learning via Minibatch Proximal Update

no code implementations NeurIPS 2019 Pan Zhou, Xiao-Tong Yuan, Huan Xu, Shuicheng Yan, Jiashi Feng

We address the problem of meta-learning which learns a prior over hypothesis from a sample of meta-training tasks for fast adaptation on meta-testing tasks.

Few-Shot Learning

Classification Calibration for Long-tail Instance Segmentation

1 code implementation29 Oct 2019 Tao Wang, Yu Li, Bingyi Kang, Junnan Li, Jun Hao Liew, Sheng Tang, Steven Hoi, Jiashi Feng

In this report, we investigate the performance drop phenomenon of state-of-the-art two-stage instance segmentation models when processing extreme long-tail training data based on the LVIS [5] dataset, and find a major cause is the inaccurate classification of object proposals.

Classification General Classification +3

On Robustness of Neural Ordinary Differential Equations

2 code implementations ICLR 2020 Hanshu Yan, Jiawei Du, Vincent Y. F. Tan, Jiashi Feng

We then provide an insightful understanding of this phenomenon by exploiting a certain desirable property of the flow of a continuous-time ODE, namely that integral curves are non-intersecting.

Adversarial Attack

Compressed Video Action Recognition with Refined Motion Vector

no code implementations6 Oct 2019 Haoyuan Cao, Shining Yu, Jiashi Feng

Although CNN has reached satisfactory performance in image-related tasks, using CNN to process videos is much more challenging due to the enormous size of raw video streams.

Action Recognition Optical Flow Estimation +2

Adaptive ROI Generation for Video Object Segmentation Using Reinforcement Learning

1 code implementation27 Sep 2019 Mingjie Sun, Jimin Xiao, Eng Gee Lim, Yanchu Xie, Jiashi Feng

In this paper, we aim to tackle the task of semi-supervised video object segmentation across a sequence of frames where only the ground-truth segmentation of the first frame is provided.

reinforcement-learning Reinforcement Learning (RL) +4

Hierarchical Neural Architecture Search via Operator Clustering

1 code implementation26 Sep 2019 Guilin Li, Xing Zhang, Zitong Wang, Matthias Tan, Jiashi Feng, Zhenguo Li, Tong Zhang

Recently, the efficiency of automatic neural architecture design has been significantly improved by gradient-based search methods such as DARTS.

Clustering