Search Results for author: Hongsheng Li

Found 194 papers, 112 papers with code

RBF-Softmax: Learning Deep Representative Prototypes with Radial Basis Function Softmax

1 code implementation ECCV 2020 Xiao Zhang, Rui Zhao, Yu Qiao, Hongsheng Li

To address this problem, this paper introduces a novel Radial Basis Function (RBF) distances to replace the commonly used inner products in the softmax loss function, such that it can adaptively assign losses to regularize the intra-class and inter-class distances by reshaping the relative differences, and thus creating more representative prototypes of classes to improve optimization.

Better Aligning Text-to-Image Models with Human Preference

no code implementations25 Mar 2023 Xiaoshi Wu, Keqiang Sun, Feng Zhu, Rui Zhao, Hongsheng Li

Using the HPS, we propose a simple yet effective method to adapt Stable Diffusion to better align with human aesthetic preferences.

CORA: Adapting CLIP for Open-Vocabulary Detection with Region Prompting and Anchor Pre-Matching

1 code implementation23 Mar 2023 Xiaoshi Wu, Feng Zhu, Rui Zhao, Hongsheng Li

To overcome these obstacles, we propose CORA, a DETR-style framework that adapts CLIP for Open-vocabulary detection by Region prompting and Anchor pre-matching.

 Ranked #1 on Open Vocabulary Object Detection on MSCOCO (using extra training data)

object-detection Object Localization +1

Towards Better 3D Knowledge Transfer via Masked Image Modeling for Multi-view 3D Understanding

no code implementations20 Mar 2023 Jihao Liu, Tai Wang, Boxiao Liu, Qihang Zhang, Yu Liu, Hongsheng Li

In this paper, we propose Geometry Enhanced Masked Image Modeling (GeoMIM) to transfer the knowledge of the LiDAR model in a pretrain-finetune paradigm for improving the multi-view camera-based 3D detection.

3D Object Detection object-detection +1

VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow Estimation

no code implementations15 Mar 2023 Xiaoyu Shi, Zhaoyang Huang, Weikang Bian, Dasong Li, Manyuan Zhang, Ka Chun Cheung, Simon See, Hongwei Qin, Jifeng Dai, Hongsheng Li

We first propose a TRi-frame Optical Flow (TROF) module that estimates bi-directional optical flows for the center frame in a three-frame manner.

Optical Flow Estimation

Parameter is Not All You Need: Starting from Non-Parametric Networks for 3D Point Cloud Analysis

2 code implementations14 Mar 2023 Renrui Zhang, Liuhui Wang, Yali Wang, Peng Gao, Hongsheng Li, Jianbo Shi

We present a Non-parametric Network for 3D point cloud analysis, Point-NN, which consists of purely non-learnable components: farthest point sampling (FPS), k-nearest neighbors (k-NN), and pooling operations, with trigonometric functions.

3D Point Cloud Classification Training-free 3D Part Segmentation +1

PATS: Patch Area Transportation with Subdivision for Local Feature Matching

no code implementations14 Mar 2023 Junjie Ni, Yijin Li, Zhaoyang Huang, Hongsheng Li, Hujun Bao, Zhaopeng Cui, Guofeng Zhang

However, estimating scale differences between these patches is non-trivial since the scale differences are determined by both relative camera poses and scene structures, and thus spatially varying over image pairs.

Graph Matching Optical Flow Estimation +2

Mimic before Reconstruct: Enhancing Masked Autoencoders with Feature Mimicking

1 code implementation9 Mar 2023 Peng Gao, Renrui Zhang, Rongyao Fang, Ziyi Lin, Hongyang Li, Hongsheng Li, Qiao Yu

To alleviate this, previous methods simply replace the pixel reconstruction targets of 75% masked tokens by encoded features from pre-trained image-image (DINO) or image-language (CLIP) contrastive learning.

Contrastive Learning

KBNet: Kernel Basis Network for Image Restoration

1 code implementation6 Mar 2023 Yi Zhang, Dasong Li, Xiaoyu Shi, Dailan He, Kangning Song, Xiaogang Wang, Hongwei Qin, Hongsheng Li

In this paper, we propose a kernel basis attention (KBA) module, which introduces learnable kernel bases to model representative image patterns for spatial information aggregation.

Color Image Denoising Deblurring +4

Prompt, Generate, then Cache: Cascade of Foundation Models makes Strong Few-shot Learners

2 code implementations3 Mar 2023 Renrui Zhang, Xiangfei Hu, Bohao Li, Siyuan Huang, Hanqiu Deng, Hongsheng Li, Yu Qiao, Peng Gao

Our CaFo incorporates CLIP's language-contrastive knowledge, DINO's vision-contrastive knowledge, DALL-E's vision-generative knowledge, and GPT-3's language-generative knowledge.

Few-Shot Learning Representation Learning

ConQueR: Query Contrast Voxel-DETR for 3D Object Detection

1 code implementation14 Dec 2022 Benjin Zhu, Zhe Wang, Shaoshuai Shi, Hang Xu, Lanqing Hong, Hongsheng Li

We thus propose a Query Contrast mechanism to explicitly enhance queries towards their best-matched GTs over all unmatched query predictions.

3D Object Detection object-detection

CGOF++: Controllable 3D Face Synthesis with Conditional Generative Occupancy Fields

no code implementations23 Nov 2022 Keqiang Sun, Shangzhe Wu, Ning Zhang, Zhaoyang Huang, Quan Wang, Hongsheng Li

Capitalizing on the recent advances in image generation models, existing controllable face image synthesis methods are able to generate high-fidelity images with some levels of controllability, e. g., controlling the shapes, expressions, textures, and poses of the generated face images.

Face Generation

Teach-DETR: Better Training DETR with Teachers

1 code implementation22 Nov 2022 Linjiang Huang, Kaixin Lu, Guanglu Song, Liang Wang, Si Liu, Yu Liu, Hongsheng Li

In this paper, we present a novel training scheme, namely Teach-DETR, to learn better DETR-based detectors from versatile teacher detectors.

Uni-Perceiver v2: A Generalist Model for Large-Scale Vision and Vision-Language Tasks

1 code implementation17 Nov 2022 Hao Li, Jinguo Zhu, Xiaohu Jiang, Xizhou Zhu, Hongsheng Li, Chun Yuan, Xiaohua Wang, Yu Qiao, Xiaogang Wang, Wenhai Wang, Jifeng Dai

In this paper, we propose Uni-Perceiver v2, which is the first generalist model capable of handling major large-scale vision and vision-language tasks with competitive performance.

Language Modelling Multi-Task Learning

InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions

2 code implementations10 Nov 2022 Wenhai Wang, Jifeng Dai, Zhe Chen, Zhenhang Huang, Zhiqi Li, Xizhou Zhu, Xiaowei Hu, Tong Lu, Lewei Lu, Hongsheng Li, Xiaogang Wang, Yu Qiao

Compared to the great progress of large-scale vision transformers (ViTs) in recent years, large-scale models based on convolutional neural networks (CNNs) are still in an early state.

2D object detection Classification +3

Collaboration of Pre-trained Models Makes Better Few-shot Learner

no code implementations25 Sep 2022 Renrui Zhang, Bohao Li, Wei zhang, Hao Dong, Hongsheng Li, Peng Gao, Yu Qiao

In this paper, we propose CoMo, a Collaboration of pre-trained Models that incorporates diverse prior knowledge from various pre-training paradigms for better few-shot learning.

Few-Shot Learning Representation Learning

Magnetic Resonance Fingerprinting with compressed sensing and distance metric learning

no code implementations19 Sep 2022 Zhe Wang, Hongsheng Li, Qinwei Zhang, Jing Yuan, Xiaogang Wang

Adaptively learning a distance metric from the undersampled training data can significantly improve the matching accuracy of the query fingerprints.

Magnetic Resonance Fingerprinting Metric Learning

NeuralMarker: A Framework for Learning General Marker Correspondence

no code implementations19 Sep 2022 Zhaoyang Huang, Xiaokun Pan, Weihong Pan, Weikang Bian, Yan Xu, Ka Chun Cheung, Guofeng Zhang, Hongsheng Li

We tackle the problem of estimating correspondences from a general marker, such as a movie poster, to an image that captures such a marker.

Video Editing

Towards Robust Face Recognition with Comprehensive Search

no code implementations29 Aug 2022 Manyuan Zhang, Guanglu Song, Yu Liu, Hongsheng Li

To eliminate the bias of single-aspect research and provide an overall understanding of the face recognition model design, we first carefully design the search space for each aspect, then a comprehensive search method is introduced to jointly search optimal data cleaning, architecture, and loss function design.

Face Recognition Robust Face Recognition

Frozen CLIP Models are Efficient Video Learners

2 code implementations6 Aug 2022 Ziyi Lin, Shijie Geng, Renrui Zhang, Peng Gao, Gerard de Melo, Xiaogang Wang, Jifeng Dai, Yu Qiao, Hongsheng Li

Video recognition has been dominated by the end-to-end learning paradigm -- first initializing a video recognition model with weights of a pretrained image model and then conducting end-to-end training on videos.

Ranked #14 on Action Classification on Kinetics-400 (using extra training data)

Action Classification Video Recognition

Tip-Adapter: Training-free Adaption of CLIP for Few-shot Classification

2 code implementations19 Jul 2022 Renrui Zhang, Zhang Wei, Rongyao Fang, Peng Gao, Kunchang Li, Jifeng Dai, Yu Qiao, Hongsheng Li

On top of that, the performance of Tip-Adapter can be further boosted to be state-of-the-art on ImageNet by fine-tuning the cache model for 10$\times$ fewer epochs than existing methods, which is both effective and efficient.

Retrieval Transfer Learning

TokenMix: Rethinking Image Mixing for Data Augmentation in Vision Transformers

1 code implementation18 Jul 2022 Jihao Liu, Boxiao Liu, Hang Zhou, Hongsheng Li, Yu Liu

In this paper, we propose a novel data augmentation technique TokenMix to improve the performance of vision transformers.

Data Augmentation

UniNet: Unified Architecture Search with Convolution, Transformer, and MLP

2 code implementations12 Jul 2022 Jihao Liu, Xin Huang, Guanglu Song, Hongsheng Li, Yu Liu

Finally, we integrate configurable operators and DSMs into a unified search space and search with a Reinforcement Learning-based search algorithm to fully explore the optimal combination of the operators.

Image Classification Neural Architecture Search

No Attention is Needed: Grouped Spatial-temporal Shift for Simple and Efficient Video Restorers

no code implementations22 Jun 2022 Dasong Li, Xiaoyu Shi, Yi Zhang, Xiaogang Wang, Hongwei Qin, Hongsheng Li

The key of our framework is the grouped spatial-temporal shift, which is simple and lightweight, but can implicitly establish inter-frame correspondences and achieve multi-frame aggregation.

Deblurring Denoising +3

3D Object Detection for Autonomous Driving: A Review and New Outlooks

1 code implementation19 Jun 2022 Jiageng Mao, Shaoshuai Shi, Xiaogang Wang, Hongsheng Li

Autonomous driving, in recent years, has been receiving increasing attention for its potential to relieve drivers' burdens and improve the safety of driving.

3D Object Detection Autonomous Driving

Controllable 3D Face Synthesis with Conditional Generative Occupancy Fields

no code implementations16 Jun 2022 Keqiang Sun, Shangzhe Wu, Zhaoyang Huang, Ning Zhang, Quan Wang, Hongsheng Li

Capitalizing on the recent advances in image generation models, existing controllable face image synthesis methods are able to generate high-fidelity images with some levels of controllability, e. g., controlling the shapes, expressions, textures, and poses of the generated face images.

Face Generation

Point-M2AE: Multi-scale Masked Autoencoders for Hierarchical Point Cloud Pre-training

1 code implementation28 May 2022 Renrui Zhang, Ziyu Guo, Rongyao Fang, Bin Zhao, Dong Wang, Yu Qiao, Hongsheng Li, Peng Gao

By fine-tuning on downstream tasks, Point-M2AE achieves 86. 43% accuracy on ScanObjectNN, +3. 36% to the second-best, and largely benefits the few-shot classification, part segmentation and 3D object detection with the hierarchical pre-training scheme.

3D Object Detection 3D Point Cloud Linear Classification +4

MixMIM: Mixed and Masked Image Modeling for Efficient Visual Representation Learning

1 code implementation26 May 2022 Jihao Liu, Xin Huang, Osamu Yoshie, Yu Liu, Hongsheng Li

In this study, we propose Mixed and Masked Image Modeling (MixMIM), a simple but efficient MIM method that is applicable to various hierarchical Vision Transformers.

 Ranked #1 on Object Detection on COCO 2017 (mAP metric)

Image Classification Object Detection +2

MPPNet: Multi-Frame Feature Intertwining with Proxy Points for 3D Temporal Object Detection

1 code implementation12 May 2022 Xuesong Chen, Shaoshuai Shi, Benjin Zhu, Ka Chun Cheung, Hang Xu, Hongsheng Li

Accurate and reliable 3D detection is vital for many applications including autonomous driving vehicles and service robots.

Autonomous Driving object-detection +1

Efficient Burst Raw Denoising with Variance Stabilization and Multi-frequency Denoising Network

no code implementations10 May 2022 Dasong Li, Yi Zhang, Ka Lung Law, Xiaogang Wang, Hongwei Qin, Hongsheng Li

As for each sub-network, we propose an efficient multi-frequency denoising network to remove noise of different frequencies.


ConvMAE: Masked Convolution Meets Masked Autoencoders

3 code implementations8 May 2022 Peng Gao, Teli Ma, Hongsheng Li, Ziyi Lin, Jifeng Dai, Yu Qiao

Masked auto-encoding for feature pretraining and multi-scale hybrid convolution-transformer architectures can further unleash the potentials of ViT, leading to state-of-the-art performances on image classification, detection and semantic segmentation.

Image Classification Object Detection +1

EdgeViTs: Competing Light-weight CNNs on Mobile Devices with Vision Transformers

2 code implementations6 May 2022 Junting Pan, Adrian Bulat, Fuwen Tan, Xiatian Zhu, Lukasz Dudziak, Hongsheng Li, Georgios Tzimiropoulos, Brais Martinez

In this work, pushing further along this under-studied direction we introduce EdgeViTs, a new family of light-weight ViTs that, for the first time, enable attention-based vision models to compete with the best light-weight CNNs in the tradeoff between accuracy and on-device efficiency.

Generalizable Neural Performer: Learning Robust Radiance Fields for Human Novel View Synthesis

1 code implementation25 Apr 2022 Wei Cheng, Su Xu, Jingtan Piao, Chen Qian, Wayne Wu, Kwan-Yee Lin, Hongsheng Li

Specifically, we compress the light fields for novel view human rendering as conditional implicit neural radiance fields from both geometry and appearance aspects.

Novel View Synthesis

Simulating Fluids in Real-World Still Images

1 code implementation24 Apr 2022 Siming Fan, Jingtan Piao, Chen Qian, Kwan-Yee Lin, Hongsheng Li

In this work, we tackle the problem of real-world fluid animation from a still image.

Motion Estimation

RBGNet: Ray-based Grouping for 3D Object Detection

1 code implementation CVPR 2022 Haiyang Wang, Shaoshuai Shi, Ze Yang, Rongyao Fang, Qi Qian, Hongsheng Li, Bernt Schiele, LiWei Wang

In order to learn better representations of object shape to enhance cluster features for predicting 3D boxes, we propose a ray-based feature grouping module, which aggregates the point-wise features on object surfaces using a group of determined rays uniformly emitted from cluster centers.

3D Object Detection object-detection

FlowFormer: A Transformer Architecture for Optical Flow

1 code implementation30 Mar 2022 Zhaoyang Huang, Xiaoyu Shi, Chao Zhang, Qiang Wang, Ka Chun Cheung, Hongwei Qin, Jifeng Dai, Hongsheng Li

We introduce optical Flow transFormer, dubbed as FlowFormer, a transformer-based neural network architecture for learning optical flow.

Optical Flow Estimation

Learning a Structured Latent Space for Unsupervised Point Cloud Completion

no code implementations CVPR 2022 Yingjie Cai, Kwan-Yee Lin, Chao Zhang, Qiang Wang, Xiaogang Wang, Hongsheng Li

Specifically, we map a series of related partial point clouds into multiple complete shape and occlusion code pairs and fuse the codes to obtain their representations in the unified latent space.

Point Cloud Completion

MonoDETR: Depth-guided Transformer for Monocular 3D Object Detection

1 code implementation24 Mar 2022 Renrui Zhang, Han Qiu, Tai Wang, Ziyu Guo, Xuanzhuo Xu, Yu Qiao, Peng Gao, Hongsheng Li

In this paper, we introduce a novel framework for Monocular DEtection with a depth-guided TRansformer, named MonoDETR.

Autonomous Driving Monocular 3D Object Detection +1

LiDAR-based 4D Panoptic Segmentation via Dynamic Shifting Network

1 code implementation14 Mar 2022 Fangzhou Hong, Hui Zhou, Xinge Zhu, Hongsheng Li, Ziwei Liu

In this work, we address the task of LiDAR-based panoptic segmentation, which aims to parse both objects and scenes in a unified manner.

Autonomous Driving Panoptic Segmentation

Weakly Supervised Temporal Action Localization via Representative Snippet Knowledge Propagation

1 code implementation CVPR 2022 Linjiang Huang, Liang Wang, Hongsheng Li

Our method seeks to mine the representative snippets in each video for propagating information between video snippets to generate better pseudo labels.

Pseudo Label Weakly-supervised Temporal Action Localization +1

Robust Self-Supervised LiDAR Odometry via Representative Structure Discovery and 3D Inherent Error Modeling

1 code implementation27 Feb 2022 Yan Xu, Junyi Lin, Jianping Shi, Guofeng Zhang, Xiaogang Wang, Hongsheng Li

The correct ego-motion estimation basically relies on the understanding of correspondences between adjacent LiDAR scans.

Motion Estimation

Meta Knowledge Distillation

no code implementations16 Feb 2022 Jihao Liu, Boxiao Liu, Hongsheng Li, Yu Liu

Recent studies pointed out that knowledge distillation (KD) suffers from two degradation problems, the teacher-student gap and the incompatibility with strong data augmentations, making it not applicable to training state-of-the-art models, which are trained with advanced augmentations.

Data Augmentation Image Classification +1

Distillation with Contrast is All You Need for Self-Supervised Point Cloud Representation Learning

no code implementations9 Feb 2022 Kexue Fu, Peng Gao, Renrui Zhang, Hongsheng Li, Yu Qiao, Manning Wang

Especially, we develop a variant of ViT for 3D point cloud feature extraction, which also achieves comparable results with existing backbones when combined with our framework, and visualization of the attention maps show that our model does understand the point cloud by combining the global shape information and multiple local structural information, which is consistent with the inspiration of our representation learning method.

Contrastive Learning Knowledge Distillation +1

UniFormer: Unifying Convolution and Self-attention for Visual Recognition

5 code implementations24 Jan 2022 Kunchang Li, Yali Wang, Junhao Zhang, Peng Gao, Guanglu Song, Yu Liu, Hongsheng Li, Yu Qiao

Different from the typical transformer blocks, the relation aggregators in our UniFormer block are equipped with local and global token affinity respectively in shallow and deep layers, allowing to tackle both redundancy and dependency for efficient and effective representation learning.

Image Classification object-detection +5

UniFormer: Unified Transformer for Efficient Spatiotemporal Representation Learning

2 code implementations12 Jan 2022 Kunchang Li, Yali Wang, Peng Gao, Guanglu Song, Yu Liu, Hongsheng Li, Yu Qiao

For Something-Something V1 and V2, our UniFormer achieves new state-of-the-art performances of 60. 9% and 71. 2% top-1 accuracy respectively.

Representation Learning

Pyramid Fusion Transformer for Semantic Segmentation

no code implementations11 Jan 2022 Zipeng Qin, Jianbo Liu, Xiaolin Zhang, Maoqing Tian, Aojun Zhou, Shuai Yi, Hongsheng Li

The recently proposed MaskFormer gives a refreshed perspective on the task of semantic segmentation: it shifts from the popular pixel-level classification paradigm to a mask-level classification method.

Semantic Segmentation

PointCLIP: Point Cloud Understanding by CLIP

2 code implementations CVPR 2022 Renrui Zhang, Ziyu Guo, Wei zhang, Kunchang Li, Xupeng Miao, Bin Cui, Yu Qiao, Peng Gao, Hongsheng Li

On top of that, we design an inter-view adapter to better extract the global feature and adaptively fuse the few-shot knowledge learned from 3D into CLIP pre-trained in 2D.

Ranked #3 on Training-free 3D Part Segmentation on ShapeNet-Part (using extra training data)

Few-Shot Learning Training-free 3D Part Segmentation +3

Uni-Perceiver: Pre-training Unified Architecture for Generic Perception for Zero-shot and Few-shot Tasks

1 code implementation CVPR 2022 Xizhou Zhu, Jinguo Zhu, Hao Li, Xiaoshi Wu, Xiaogang Wang, Hongsheng Li, Xiaohua Wang, Jifeng Dai

The model is pre-trained on several uni-modal and multi-modal tasks, and evaluated on a variety of downstream tasks, including novel tasks that did not appear in the pre-training stage.

DominoSearch: Find layer-wise fine-grained N:M sparse schemes from dense neural networks

1 code implementation NeurIPS 2021 Wei Sun, Aojun Zhou, Sander Stuijk, Rob Wijnhoven, Andrew Oakleigh Nelson, Hongsheng Li, Henk Corporaal

However, the existing N:M algorithms only address the challenge of how to train N:M sparse neural networks in a uniform fashion (i. e. every layer has the same N:M sparsity) and suffer from a significant accuracy drop for high sparsity (i. e. when sparsity > 80\%).

Network Pruning

Container: Context Aggregation Networks

1 code implementation NeurIPS 2021 Peng Gao, Jiasen Lu, Hongsheng Li, Roozbeh Mottaghi, Aniruddha Kembhavi

Convolutional neural networks (CNNs) are ubiquitous in computer vision, with a myriad of effective and efficient variations.

Inductive Bias Instance Segmentation +4

IDR: Self-Supervised Image Denoising via Iterative Data Refinement

1 code implementation CVPR 2022 Yi Zhang, Dasong Li, Ka Lung Law, Xiaogang Wang, Hongwei Qin, Hongsheng Li

To evaluate raw image denoising performance in real-world applications, we build a high-quality raw image dataset SenseNoise-500 that contains 500 real-life scenes.

Image Denoising

A Simple Long-Tailed Recognition Baseline via Vision-Language Model

1 code implementation29 Nov 2021 Teli Ma, Shijie Geng, Mengmeng Wang, Jing Shao, Jiasen Lu, Hongsheng Li, Peng Gao, Yu Qiao

Recent advances in large-scale contrastive visual-language pretraining shed light on a new pathway for visual recognition.

Ranked #2 on Long-tail Learning on Places-LT (using extra training data)

Contrastive Learning Language Modelling +3

Tip-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling

1 code implementation6 Nov 2021 Renrui Zhang, Rongyao Fang, Wei zhang, Peng Gao, Kunchang Li, Jifeng Dai, Yu Qiao, Hongsheng Li

To further enhance CLIP's few-shot capability, CLIP-Adapter proposed to fine-tune a lightweight residual feature adapter and significantly improves the performance for few-shot classification.

Language Modelling Transfer Learning

Rethinking Noise Synthesis and Modeling in Raw Denoising

1 code implementation ICCV 2021 Yi Zhang, Hongwei Qin, Xiaogang Wang, Hongsheng Li

However, the real raw image noise is contributed by many noise sources and varies greatly among different sensors.

Image Denoising

CLIP-Adapter: Better Vision-Language Models with Feature Adapters

1 code implementation9 Oct 2021 Peng Gao, Shijie Geng, Renrui Zhang, Teli Ma, Rongyao Fang, Yongfeng Zhang, Hongsheng Li, Yu Qiao

Large-scale contrastive vision-language pre-training has shown significant progress in visual representation learning.

Prompt Engineering Representation Learning

UniNet: Unified Architecture Search with Convolution, Transformer, and MLP

no code implementations8 Oct 2021 Jihao Liu, Hongsheng Li, Guanglu Song, Xin Huang, Yu Liu

Recently, transformer and multi-layer perceptron (MLP) architectures have achieved impressive results on various vision tasks.

Image Classification object-detection +2

Encoder-decoder with Multi-level Attention for 3D Human Shape and Pose Estimation

1 code implementation ICCV 2021 Ziniu Wan, Zhengjia Li, Maoqing Tian, Jianbo Liu, Shuai Yi, Hongsheng Li

To this end, we propose Multi-level Attention Encoder-Decoder Network (MAED), including a Spatial-Temporal Encoder (STE) and a Kinematic Topology Decoder (KTD) to model multi-level attentions in a unified framework.

 Ranked #1 on 3D Human Pose Estimation on MPI-INF-3DHP (PA-MPJPE metric)

3D Absolute Human Pose Estimation

Spatio-Temporal Interaction Graph Parsing Networks for Human-Object Interaction Recognition

no code implementations19 Aug 2021 Ning Wang, Guangming Zhu, Liang Zhang, Peiyi Shen, Hongsheng Li, Cong Hua

With the effective spatio-temporal relationship modeling, it is possible not only to uncover contextual information in each frame but also to directly capture inter-time dependencies.

Human-Object Interaction Detection

LIGA-Stereo: Learning LiDAR Geometry Aware Representations for Stereo-based 3D Detector

1 code implementation ICCV 2021 Xiaoyang Guo, Shaoshuai Shi, Xiaogang Wang, Hongsheng Li

Compared with the state-of-the-art stereo detector, our method has improved the 3D detection performance of cars, pedestrians, cyclists by 10. 44%, 5. 69%, 5. 97% mAP respectively on the official KITTI benchmark.

3D Object Detection From Stereo Images Stereo Matching

LIF-Seg: LiDAR and Camera Image Fusion for 3D LiDAR Semantic Segmentation

no code implementations17 Aug 2021 Lin Zhao, Hui Zhou, Xinge Zhu, Xiao Song, Hongsheng Li, Wenbing Tao

However, two major issues of the fusion between camera and LiDAR hinder its performance, \ie, how to effectively fuse these two modalities and how to precisely align them (suffering from the weak spatiotemporal synchronization problem).

Autonomous Driving LIDAR Semantic Segmentation +1

ST3D++: Denoised Self-training for Unsupervised Domain Adaptation on 3D Object Detection

no code implementations15 Aug 2021 Jihan Yang, Shaoshuai Shi, Zhe Wang, Hongsheng Li, Xiaojuan Qi

These specific designs enable the detector to be trained on meticulously refined pseudo labeled target data with denoised training signals, and thus effectively facilitate adapting an object detector to a target domain without requiring annotations.

3D Object Detection Data Augmentation +4

Foreground-Action Consistency Network for Weakly Supervised Temporal Action Localization

1 code implementation ICCV 2021 Linjiang Huang, Liang Wang, Hongsheng Li

In this paper, we present a framework named FAC-Net based on the I3D backbone, on which three branches are appended, named class-wise foreground classification branch, class-agnostic attention branch and multiple instance learning branch.

Multiple Instance Learning Video Understanding +2

Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency

1 code implementation ICCV 2021 Zhipeng Luo, Zhongang Cai, Changqing Zhou, Gongjie Zhang, Haiyu Zhao, Shuai Yi, Shijian Lu, Hongsheng Li, Shanghang Zhang, Ziwei Liu

In addition, existing 3D domain adaptive detection methods often assume prior access to the target domain annotations, which is rarely feasible in the real world.

3D Object Detection Autonomous Driving +1

Hybrid Supervision Learning for Pathology Whole Slide Image Classification

1 code implementation2 Jul 2021 Jiahui Li, Wen Chen, Xiaodi Huang, Zhiqiang Hu, Qi Duan, Hongsheng Li, Dimitris N. Metaxas, Shaoting Zhang

To handle this problem, we propose a hybrid supervision learning framework for this kind of high resolution images with sufficient image-level coarse annotations and a few pixel-level fine labels.

Classification Image Classification +3

Refining Pseudo Labels with Clustering Consensus over Generations for Unsupervised Object Re-identification

1 code implementation CVPR 2021 Xiao Zhang, Yixiao Ge, Yu Qiao, Hongsheng Li

Unsupervised object re-identification targets at learning discriminative representations for object retrieval without any annotations.

Pseudo Label Retrieval

Scalable Transformers for Neural Machine Translation

no code implementations4 Jun 2021 Peng Gao, Shijie Geng, Yu Qiao, Xiaogang Wang, Jifeng Dai, Hongsheng Li

In this paper, we propose a novel Scalable Transformers, which naturally contains sub-Transformers of different scales and have shared parameters.

Machine Translation NMT +1

Container: Context Aggregation Network

2 code implementations2 Jun 2021 Peng Gao, Jiasen Lu, Hongsheng Li, Roozbeh Mottaghi, Aniruddha Kembhavi

Convolutional neural networks (CNNs) are ubiquitous in computer vision, with a myriad of effective and efficient variations.

Image Classification Inductive Bias +5

FNAS: Uncertainty-Aware Fast Neural Architecture Search

no code implementations25 May 2021 Jihao Liu, Ming Zhang, Yangting Sun, Boxiao Liu, Guanglu Song, Yu Liu, Hongsheng Li

Further, an architecture knowledge pool together with a block similarity function is proposed to utilize parameter knowledge and reduces the searching time by 2 times.

Fairness Neural Architecture Search +1

VS-Net: Voting with Segmentation for Visual Localization

1 code implementation CVPR 2021 Zhaoyang Huang, Han Zhou, Yijin Li, Bangbang Yang, Yan Xu, Xiaowei Zhou, Hujun Bao, Guofeng Zhang, Hongsheng Li

To address this problem, we propose a novel visual localization framework that establishes 2D-to-3D correspondences between the query image and the 3D map with a series of learnable scene-specific landmarks.

Semantic Segmentation Visual Localization

Inverting Generative Adversarial Renderer for Face Reconstruction

no code implementations CVPR 2021 Jingtan Piao, Keqiang Sun, KwanYee Lin, Quan Wang, Hongsheng Li

Since the GAR learns to model the complicated real-world image, instead of relying on the simplified graphics rules, it is capable of producing realistic images, which essentially inhibits the domain-shift noise in training and optimization.

Face Reconstruction

Decoupled Spatial-Temporal Transformer for Video Inpainting

1 code implementation14 Apr 2021 Rui Liu, Hanming Deng, Yangyi Huang, Xiaoyu Shi, Lewei Lu, Wenxiu Sun, Xiaogang Wang, Jifeng Dai, Hongsheng Li

Seamless combination of these two novel designs forms a better spatial-temporal attention scheme and our proposed model achieves better performance than state-of-the-art video inpainting approaches with significant boosted efficiency.

Video Inpainting

Semantic Scene Completion via Integrating Instances and Scene in-the-Loop

1 code implementation CVPR 2021 Yingjie Cai, Xuesong Chen, Chao Zhang, Kwan-Yee Lin, Xiaogang Wang, Hongsheng Li

The key insight is that we decouple the instances from a coarsely completed semantic scene instead of a raw input image to guide the reconstruction of instances and the overall scene.

3D Semantic Scene Completion Scene Understanding

LIFE: Lighting Invariant Flow Estimation

no code implementations7 Apr 2021 Zhaoyang Huang, Xiaokun Pan, Runsen Xu, Yan Xu, Ka Chun Cheung, Guofeng Zhang, Hongsheng Li

However, local image contents are inevitably ambiguous and error-prone during the cross-image feature matching process, which hinders downstream tasks.

Fixing the Teacher-Student Knowledge Discrepancy in Distillation

no code implementations31 Mar 2021 Jiangfan Han, Mengya Gao, Yujie Wang, Quanquan Li, Hongsheng Li, Xiaogang Wang

To solve this problem, in this paper, we propose a novel student-dependent distillation method, knowledge consistent distillation, which makes teacher's knowledge more consistent with the student and provides the best suitable knowledge to different student networks for distillation.

Image Classification Knowledge Distillation +2

AutoLoss-Zero: Searching Loss Functions from Scratch for Generic Tasks

no code implementations CVPR 2022 Hao Li, Tianwen Fu, Jifeng Dai, Hongsheng Li, Gao Huang, Xizhou Zhu

However, the automatic design of loss functions for generic tasks with various evaluation metrics remains under-investigated.

DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial Network

1 code implementation CVPR 2021 Rui Liu, Yixiao Ge, Ching Lam Choi, Xiaogang Wang, Hongsheng Li

Conditional generative adversarial networks (cGANs) target at synthesizing diverse images given the input conditions and latent codes, but unfortunately, they usually suffer from the issue of mode collapse.

Contrastive Learning Image Generation

ST3D: Self-training for Unsupervised Domain Adaptation on 3D Object Detection

1 code implementation CVPR 2021 Jihan Yang, Shaoshuai Shi, Zhe Wang, Hongsheng Li, Xiaojuan Qi

Then, the detector is iteratively improved on the target domain by alternatively conducting two steps, which are the pseudo label updating with the developed quality-aware triplet memory bank and the model training with curriculum data augmentation.

3D Object Detection Data Augmentation +3

Learning N:M Fine-grained Structured Sparse Neural Networks From Scratch

4 code implementations ICLR 2021 Aojun Zhou, Yukun Ma, Junnan Zhu, Jianbo Liu, Zhijie Zhang, Kun Yuan, Wenxiu Sun, Hongsheng Li

In this paper, we are the first to study training from scratch an N:M fine-grained structured sparse network, which can maintain the advantages of both unstructured fine-grained sparsity and structured coarse-grained sparsity simultaneously on specifically designed GPUs.

Fast Convergence of DETR with Spatially Modulated Co-Attention

2 code implementations19 Jan 2021 Peng Gao, Minghang Zheng, Xiaogang Wang, Jifeng Dai, Hongsheng Li

The recently proposed Detection Transformer (DETR) model successfully applies Transformer to objects detection and achieves comparable performance with two-stage object detection frameworks, such as Faster-RCNN.

object-detection Object Detection

Progressive Correspondence Pruning by Consensus Learning

no code implementations ICCV 2021 Chen Zhao, Yixiao Ge, Feng Zhu, Rui Zhao, Hongsheng Li, Mathieu Salzmann

Correspondence selection aims to correctly select the consistent matches (inliers) from an initial set of putative correspondences.

Denoising Pose Estimation +1

Self-supervised Temporal Learning

no code implementations1 Jan 2021 Hao Shao, Yu Liu, Hongsheng Li

Inspired by spatial-based contrastive SSL, we show that significant improvement can be achieved by a proposed temporal-based contrastive learning approach, which includes three novel and efficient modules: temporal augmentations, temporal memory bank and SSTL loss.

Contrastive Learning Retrieval +3

Towards Overcoming False Positives in Visual Relationship Detection

no code implementations23 Dec 2020 Daisheng Jin, Xiao Ma, Chongzhi Zhang, Yizhuo Zhou, Jiashu Tao, Mingyuan Zhang, Haiyu Zhao, Shuai Yi, Zhoujun Li, Xianglong Liu, Hongsheng Li

We observe that during training, the relationship proposal distribution is highly imbalanced: most of the negative relationship proposals are easy to identify, e. g., the inaccurate object detection, which leads to the under-fitting of low-frequency difficult proposals.

Graph Attention Human-Object Interaction Detection +3

A Holistically-Guided Decoder for Deep Representation Learning with Applications to Semantic Segmentation and Object Detection

no code implementations18 Dec 2020 Jianbo Liu, Sijie Ren, Yuanjie Zheng, Xiaogang Wang, Hongsheng Li

With the proposed holistically-guided decoder, we implement the EfficientFCN architecture for semantic segmentation and HGD-FPN for object detection and instance segmentation.

Instance Segmentation object-detection +3

REFINE: Prediction Fusion Network for Panoptic Segmentation

no code implementations15 Dec 2020 Jiawei Ren, Cunjun Yu, Zhongang Cai, Mingyuan Zhang, Chongsong Chen, Haiyu Zhao, Shuai Yi, Hongsheng Li

Panoptic segmentation aims at generating pixel-wise class and instance predictions for each pixel in the input image, which is a challenging task and far more complicated than naively fusing the semantic and instance segmentation results.

Instance Segmentation Panoptic Segmentation

End-to-End Object Detection with Adaptive Clustering Transformer

1 code implementation18 Nov 2020 Minghang Zheng, Peng Gao, Renrui Zhang, Kunchang Li, Xiaogang Wang, Hongsheng Li, Hao Dong

In this paper, a novel variant of transformer named Adaptive Clustering Transformer(ACT) has been proposed to reduce the computation cost for high-resolution input.

object-detection Object Detection

SelfVoxeLO: Self-supervised LiDAR Odometry with Voxel-based Deep Neural Networks

no code implementations19 Oct 2020 Yan Xu, Zhaoyang Huang, Kwan-Yee Lin, Xinge Zhu, Jianping Shi, Hujun Bao, Guofeng Zhang, Hongsheng Li

To suit our network to self-supervised learning, we design several novel loss functions that utilize the inherent properties of LiDAR point clouds.

Self-Supervised Learning

PV-RCNN: The Top-Performing LiDAR-only Solutions for 3D Detection / 3D Tracking / Domain Adaptation of Waymo Open Dataset Challenges

1 code implementation28 Aug 2020 Shaoshuai Shi, Chaoxu Guo, Jihan Yang, Hongsheng Li

In this technical report, we present the top-performing LiDAR-only solutions for 3D detection, 3D tracking and domain adaptation three tracks in Waymo Open Dataset Challenges 2020.

3D Object Detection Domain Adaptation +1

EfficientFCN: Holistically-guided Decoding for Semantic Segmentation

no code implementations ECCV 2020 Jianbo Liu, Junjun He, Jiawei Zhang, Jimmy S. Ren, Hongsheng Li

State-of-the-art semantic segmentation algorithms are mostly based on dilated Fully Convolutional Networks (dilatedFCN), which adopt dilated convolutions in the backbone networks to extract high-resolution feature maps for achieving high-performance segmentation performance.

Semantic Segmentation

Multi-organ Segmentation via Co-training Weight-averaged Models from Few-organ Datasets

no code implementations17 Aug 2020 Rui Huang, Yuanjie Zheng, Zhiqiang Hu, Shaoting Zhang, Hongsheng Li

In most scenarios, one might obtain annotations of a single or a few organs from one training set, and obtain annotations of the the other organs from another set of training images.

Organ Segmentation

Cylinder3D: An Effective 3D Framework for Driving-scene LiDAR Semantic Segmentation

3 code implementations4 Aug 2020 Hui Zhou, Xinge Zhu, Xiao Song, Yuexin Ma, Zhe Wang, Hongsheng Li, Dahua Lin

A straightforward solution to tackle the issue of 3D-to-2D projection is to keep the 3D representation and process the points in the 3D space.

3D Semantic Segmentation LIDAR Semantic Segmentation

Open-Edit: Open-Domain Image Manipulation with Open-Vocabulary Instructions

1 code implementation ECCV 2020 Xihui Liu, Zhe Lin, Jianming Zhang, Handong Zhao, Quan Tran, Xiaogang Wang, Hongsheng Li

We propose a novel algorithm, named Open-Edit, which is the first attempt on open-domain image manipulation with open-vocabulary instructions.

Image Manipulation

Balanced Meta-Softmax for Long-Tailed Visual Recognition

1 code implementation NeurIPS 2020 Jiawei Ren, Cunjun Yu, Shunan Sheng, Xiao Ma, Haiyu Zhao, Shuai Yi, Hongsheng Li

In our experiments, we demonstrate that Balanced Meta-Softmax outperforms state-of-the-art long-tailed classification solutions on both visual recognition and instance segmentation tasks.

General Classification Instance Segmentation +2

Complementary Boundary Generator with Scale-Invariant Relation Modeling for Temporal Action Localization: Submission to ActivityNet Challenge 2020

no code implementations20 Jul 2020 Haisheng Su, Jinyuan Feng, Hao Shao, Zhenyu Jiang, Manyuan Zhang, Wei Wu, Yu Liu, Hongsheng Li, Junjie Yan

Specifically, in order to generate high-quality proposals, we consider several factors including the video feature encoder, the proposal generator, the proposal-proposal relations, the scale imbalance, and ensemble strategy.

Temporal Action Localization

Dynamic Graph Representation Learning for Video Dialog via Multi-Modal Shuffled Transformers

no code implementations8 Jul 2020 Shijie Geng, Peng Gao, Moitreya Chatterjee, Chiori Hori, Jonathan Le Roux, Yongfeng Zhang, Hongsheng Li, Anoop Cherian

Given an input video, its associated audio, and a brief caption, the audio-visual scene aware dialog (AVSD) task requires an agent to indulge in a question-answer dialog with a human about the audio-visual content.

Answer Generation Graph Representation Learning

1st place solution for AVA-Kinetics Crossover in AcitivityNet Challenge 2020

2 code implementations16 Jun 2020 Siyu Chen, Junting Pan, Guanglu Song, Manyuan Zhang, Hao Shao, Ziyi Lin, Jing Shao, Hongsheng Li, Yu Liu

This technical report introduces our winning solution to the spatio-temporal action localization track, AVA-Kinetics Crossover, in ActivityNet Challenge 2020.

Spatio-Temporal Action Localization Temporal Action Localization

Actor-Context-Actor Relation Network for Spatio-Temporal Action Localization

3 code implementations CVPR 2021 Junting Pan, Siyu Chen, Mike Zheng Shou, Yu Liu, Jing Shao, Hongsheng Li

We propose to explicitly model the Actor-Context-Actor Relation, which is the relation between two actors based on their interactions with the context.

Action Detection Action Recognition +3

Self-supervising Fine-grained Region Similarities for Large-scale Image Localization

3 code implementations ECCV 2020 Yixiao Ge, Haibo Wang, Feng Zhu, Rui Zhao, Hongsheng Li

The task of large-scale retrieval-based image localization is to estimate the geographical location of a query image by recognizing its nearest reference images from a city-scale dataset.

Image Retrieval Retrieval

Structured Domain Adaptation with Online Relation Regularization for Unsupervised Person Re-ID

4 code implementations14 Mar 2020 Yixiao Ge, Feng Zhu, Dapeng Chen, Rui Zhao, Xiaogang Wang, Hongsheng Li

To tackle the challenges, we propose an end-to-end structured domain adaptation framework with an online relation-consistency regularization term.

Pseudo Label Translation +2

MagnifierNet: Towards Semantic Adversary and Fusion for Person Re-identification

1 code implementation25 Feb 2020 Yushi Lan, Yu-An Liu, Maoqing Tian, Xinchi Zhou, Xuesen Zhang, Shuai Yi, Hongsheng Li

Meanwhile, we introduce "Semantic Fusion Branch" to filter out irrelevant noises by selectively fusing semantic region information sequentially.

Person Re-Identification

Structure-Feature based Graph Self-adaptive Pooling

1 code implementation30 Jan 2020 Liang Zhang, Xudong Wang, Hongsheng Li, Guangming Zhu, Peiyi Shen, Ping Li, Xiaoyuan Lu, Syed Afaq Ali Shah, Mohammed Bennamoun

To solve these problems mentioned above, we propose a novel graph self-adaptive pooling method with the following objectives: (1) to construct a reasonable pooled graph topology, structure and feature information of the graph are considered simultaneously, which provide additional veracity and objectivity in node selection; and (2) to make the pooled nodes contain sufficiently effective graph information, node feature information is aggregated before discarding the unimportant nodes; thus, the selected nodes contain information from neighbor nodes, which can enhance the use of features of the unselected nodes.

Graph Classification

Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification

2 code implementations ICLR 2020 Yixiao Ge, Dapeng Chen, Hongsheng Li

In order to mitigate the effects of noisy pseudo labels, we propose to softly refine the pseudo labels in the target domain by proposing an unsupervised framework, Mutual Mean-Teaching (MMT), to learn better features from the target domain via off-line refined hard pseudo labels and on-line refined soft pseudo labels in an alternative training manner.

Pseudo Label Unsupervised Domain Adaptation +1

PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection

6 code implementations CVPR 2020 Shaoshuai Shi, Chaoxu Guo, Li Jiang, Zhe Wang, Jianping Shi, Xiaogang Wang, Hongsheng Li

We present a novel and high-performance 3D object detection framework, named PointVoxel-RCNN (PV-RCNN), for accurate 3D object detection from point clouds.

3D Object Detection object-detection

Depth Completion from Sparse LiDAR Data with Depth-Normal Constraints

no code implementations ICCV 2019 Yan Xu, Xinge Zhu, Jianping Shi, Guofeng Zhang, Hujun Bao, Hongsheng Li

Most of existing methods directly train a network to learn a mapping from sparse depth inputs to dense depth maps, which has difficulties in utilizing the 3D geometric constraints and handling the practical sensor noises.

Autonomous Driving Depth Completion

Multi-modality Latent Interaction Network for Visual Question Answering

no code implementations ICCV 2019 Peng Gao, Haoxuan You, Zhanpeng Zhang, Xiaogang Wang, Hongsheng Li

The proposed module learns the cross-modality relationships between latent visual and language summarizations, which summarize visual regions and question into a small number of latent representations to avoid modeling uninformative individual region-word relations.

Language Modelling Question Answering +2

FocusNet: Imbalanced Large and Small Organ Segmentation with an End-to-End Deep Neural Network for Head and Neck CT Images

no code implementations28 Jul 2019 Yunhe Gao, Rui Huang, Ming Chen, Zhe Wang, Jincheng Deng, YuanYuan Chen, Yiwei Yang, Jie Zhang, Chanjuan Tao, Hongsheng Li

In this paper, we propose an end-to-end deep neural network for solving the problem of imbalanced large and small organ segmentation in head and neck (HaN) CT images.

Organ Segmentation

Signet Ring Cell Detection With a Semi-supervised Learning Framework

1 code implementation9 Jul 2019 Jiahui Li, Shuang Yang, Xiaodi Huang, Qian Da, Xiaoqun Yang, Zhiqiang Hu, Qi Duan, Chaofu Wang, Hongsheng Li

Our framework achieves accurate signet ring cell detection and can be readily applied in the clinical trails.

From Points to Parts: 3D Object Detection from Point Cloud with Part-aware and Part-aggregation Network

5 code implementations8 Jul 2019 Shaoshuai Shi, Zhe Wang, Jianping Shi, Xiaogang Wang, Hongsheng Li

3D object detection from LiDAR point cloud is a challenging problem in 3D scene understanding and has many practical applications.

3D Object Detection object-detection +1

Generalizing Monocular 3D Human Pose Estimation in the Wild

1 code implementation11 Apr 2019 Luyang Wang, Yan Chen, Zhenhua Guo, Keyuan Qian, Mude Lin, Hongsheng Li, Jimmy S. Ren

We observe that recent innovation in this area mainly focuses on new techniques that explicitly address the generalization issue when using this dataset, because this database is constructed in a highly controlled environment with limited human subjects and background variations.

3D Pose Estimation Monocular 3D Human Pose Estimation

Conditional Adversarial Generative Flow for Controllable Image Synthesis

no code implementations CVPR 2019 Rui Liu, Yu Liu, Xinyu Gong, Xiaogang Wang, Hongsheng Li

Flow-based generative models show great potential in image synthesis due to its reversible pipeline and exact log-likelihood target, yet it suffers from weak ability for conditional image synthesis, especially for multi-label or unaware conditions.

Image Generation

Group-wise Correlation Stereo Network

1 code implementation CVPR 2019 Xiaoyang Guo, Kai Yang, Wukui Yang, Xiaogang Wang, Hongsheng Li

Previous works built cost volumes with cross-correlation or concatenation of left and right features across all disparity levels, and then a 2D or 3D convolutional neural network is utilized to regress the disparity maps.

Autonomous Driving Stereo Matching +1

Unsupervised Cross-spectral Stereo Matching by Learning to Synthesize

1 code implementation4 Mar 2019 Mingyang Liang, Xiaoyang Guo, Hongsheng Li, Xiaogang Wang, You Song

Unsupervised cross-spectral stereo matching aims at recovering disparity given cross-spectral image pairs without any supervision in the form of ground truth disparity or depth.

Image-to-Image Translation Stereo Matching +2

Improving Referring Expression Grounding with Cross-modal Attention-guided Erasing

no code implementations CVPR 2019 Xihui Liu, ZiHao Wang, Jing Shao, Xiaogang Wang, Hongsheng Li

Referring expression grounding aims at locating certain objects or persons in an image with a referring expression, where the key challenge is to comprehend and align various types of information from visual and textual domain, such as visual attributes, location and interactions with surrounding regions.

Referring Expression

A^2-Net: Molecular Structure Estimation from Cryo-EM Density Volumes

no code implementations3 Jan 2019 Kui Xu, Zhe Wang, Jiangping Shi, Hongsheng Li, Qiangfeng Cliff Zhang

Constructing of molecular structural models from Cryo-Electron Microscopy (Cryo-EM) density volumes is the critical last step of structure determination by Cryo-EM technologies.

Pose Estimation Translation

Dynamic Fusion with Intra- and Inter- Modality Attention Flow for Visual Question Answering

no code implementations13 Dec 2018 Gao Peng, Zhengkai Jiang, Haoxuan You, Pan Lu, Steven Hoi, Xiaogang Wang, Hongsheng Li

It can robustly capture the high-level interactions between language and vision domains, thus significantly improves the performance of visual question answering.

Question Answering Visual Question Answering +1

FD-GAN: Pose-guided Feature Distilling GAN for Robust Person Re-identification

2 code implementations NeurIPS 2018 Yixiao Ge, Zhuowan Li, Haiyu Zhao, Guojun Yin, Shuai Yi, Xiaogang Wang, Hongsheng Li

Our proposed FD-GAN achieves state-of-the-art performance on three person reID datasets, which demonstrates that the effectiveness and robust feature distilling capability of the proposed FD-GAN.

Person Re-Identification