Search Results for author: Ying Shan

Found 152 papers, 86 papers with code

ConTex-Human: Free-View Rendering of Human from a Single Image with Texture-Consistent Synthesis

no code implementations28 Nov 2023 Xiangjun Gao, Xiaoyu Li, Chaopeng Zhang, Qi Zhang, YanPei Cao, Ying Shan, Long Quan

In this work, we propose a method to address the challenge of rendering a 3D human from a single image in a free-view manner.

SEED-Bench-2: Benchmarking Multimodal Large Language Models

1 code implementation28 Nov 2023 Bohao Li, Yuying Ge, Yixiao Ge, Guangzhi Wang, Rui Wang, Ruimao Zhang, Ying Shan

Multimodal large language models (MLLMs), building upon the foundation of powerful large language models (LLMs), have recently demonstrated exceptional capabilities in generating not only texts but also images given interleaved multimodal inputs (acting like a combination of GPT-4V and DALL-E 3).

Benchmarking Image Generation +1

HumanGaussian: Text-Driven 3D Human Generation with Gaussian Splatting

no code implementations28 Nov 2023 Xian Liu, Xiaohang Zhan, Jiaxiang Tang, Ying Shan, Gang Zeng, Dahua Lin, Xihui Liu, Ziwei Liu

In this paper, we propose an efficient yet effective framework, HumanGaussian, that generates high-quality 3D humans with fine-grained geometry and realistic appearance.

HumanRef: Single Image to 3D Human Generation via Reference-Guided Diffusion

no code implementations28 Nov 2023 Jingbo Zhang, Xiaoyu Li, Qi Zhang, YanPei Cao, Ying Shan, Jing Liao

Optimization-based methods that lift text-to-image diffusion models to 3D generation often fail to preserve the texture details of the reference image, resulting in inconsistent appearances in different views.

Image to 3D

UniRepLKNet: A Universal Perception Large-Kernel ConvNet for Audio, Video, Point Cloud, Time-Series and Image Recognition

1 code implementation27 Nov 2023 Xiaohan Ding, Yiyuan Zhang, Yixiao Ge, Sijie Zhao, Lin Song, Xiangyu Yue, Ying Shan

1) We propose four architectural guidelines for designing large-kernel ConvNets, the core of which is to exploit the essential characteristics of large kernels that distinguish them from small kernels - they can see wide without going deep.

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

Image Classification Object Detection +3

ViT-Lens-2: Gateway to Omni-modal Intelligence

1 code implementation27 Nov 2023 Weixian Lei, Yixiao Ge, Kun Yi, Jianfeng Zhang, Difei Gao, Dylan Sun, Yuying Ge, Ying Shan, Mike Zheng Shou

In this paper, we present ViT-Lens-2 that facilitates efficient omni-modal representation learning by perceiving novel modalities with a pretrained ViT and aligning them to a pre-defined space.

EEG Image Generation +2

GS-IR: 3D Gaussian Splatting for Inverse Rendering

1 code implementation26 Nov 2023 Zhihao Liang, Qi Zhang, Ying Feng, Ying Shan, Kui Jia

We propose GS-IR, a novel inverse rendering approach based on 3D Gaussian Splatting (GS) that leverages forward mapping volume rendering to achieve photorealistic novel view synthesis and relighting results.

Inverse Rendering Novel View Synthesis

Vision-Language Instruction Tuning: A Review and Analysis

1 code implementation14 Nov 2023 Chen Li, Yixiao Ge, Dian Li, Ying Shan

Instruction tuning is a crucial supervised training phase in Large Language Models (LLMs), aiming to enhance the LLM's ability to generalize instruction execution and adapt to user preferences.

SemanticBoost: Elevating Motion Generation with Augmented Textual Cues

no code implementations31 Oct 2023 Xin He, Shaoli Huang, Xiaohang Zhan, Chao Weng, Ying Shan

Our framework comprises a Semantic Enhancement module and a Context-Attuned Motion Denoiser (CAMD).

VideoCrafter1: Open Diffusion Models for High-Quality Video Generation

2 code implementations30 Oct 2023 Haoxin Chen, Menghan Xia, Yingqing He, Yong Zhang, Xiaodong Cun, Shaoshu Yang, Jinbo Xing, Yaofang Liu, Qifeng Chen, Xintao Wang, Chao Weng, Ying Shan

The I2V model is designed to produce videos that strictly adhere to the content of the provided reference image, preserving its content, structure, and style.

Video Generation

FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling

1 code implementation23 Oct 2023 Haonan Qiu, Menghan Xia, Yong Zhang, Yingqing He, Xintao Wang, Ying Shan, Ziwei Liu

With the availability of large-scale video datasets and the advances of diffusion models, text-driven video generation has achieved substantial progress.

Video Generation

TapMo: Shape-aware Motion Generation of Skeleton-free Characters

no code implementations19 Oct 2023 Jiaxu Zhang, Shaoli Huang, Zhigang Tu, Xin Chen, Xiaohang Zhan, Gang Yu, Ying Shan

In this work, we present TapMo, a Text-driven Animation Pipeline for synthesizing Motion in a broad spectrum of skeleton-free 3D characters.

DynVideo-E: Harnessing Dynamic NeRF for Large-Scale Motion- and View-Change Human-Centric Video Editing

no code implementations16 Oct 2023 Jia-Wei Liu, Yan-Pei Cao, Jay Zhangjie Wu, Weijia Mao, YuChao Gu, Rui Zhao, Jussi Keppo, Ying Shan, Mike Zheng Shou

Despite remarkable research advances in diffusion-based video editing, existing methods are limited to short-length videos due to the contradiction between long-range consistency and frame-wise editing.

Style Transfer Super-Resolution +1

ScaleCrafter: Tuning-free Higher-Resolution Visual Generation with Diffusion Models

1 code implementation11 Oct 2023 Yingqing He, Shaoshu Yang, Haoxin Chen, Xiaodong Cun, Menghan Xia, Yong Zhang, Xintao Wang, Ran He, Qifeng Chen, Ying Shan

Our work also suggests that a pre-trained diffusion model trained on low-resolution images can be directly used for high-resolution visual generation without further tuning, which may provide insights for future research on ultra-high-resolution image and video synthesis.

Image Generation

HiFi-123: Towards High-fidelity One Image to 3D Content Generation

no code implementations10 Oct 2023 Wangbo Yu, Li Yuan, Yan-Pei Cao, Xiangjun Gao, Xiaoyu Li, Long Quan, Ying Shan, Yonghong Tian

Recent advances in text-to-image diffusion models have enabled 3D generation from a single image.

Image to 3D

Making LLaMA SEE and Draw with SEED Tokenizer

1 code implementation2 Oct 2023 Yuying Ge, Sijie Zhao, Ziyun Zeng, Yixiao Ge, Chen Li, Xintao Wang, Ying Shan

We identify two crucial design principles: (1) Image tokens should be independent of 2D physical patch positions and instead be produced with a 1D causal dependency, exhibiting intrinsic interdependence that aligns with the left-to-right autoregressive prediction mechanism in LLMs.

multimodal generation

Anti-Aliased Neural Implicit Surfaces with Encoding Level of Detail

no code implementations19 Sep 2023 Yiyu Zhuang, Qi Zhang, Ying Feng, Hao Zhu, Yao Yao, Xiaoyu Li, Yan-Pei Cao, Ying Shan, Xun Cao

Drawing inspiration from voxel-based representations with the level of detail (LoD), we introduce a multi-scale tri-plane-based scene representation that is capable of capturing the LoD of the signed distance function (SDF) and the space radiance.

Surface Reconstruction

Speech2Lip: High-fidelity Speech to Lip Generation by Learning from a Short Video

no code implementations ICCV 2023 Xiuzhe Wu, Pengfei Hu, Yang Wu, Xiaoyang Lyu, Yan-Pei Cao, Ying Shan, Wenming Yang, Zhongqian Sun, Xiaojuan Qi

Therefore, directly learning a mapping function from speech to the entire head image is prone to ambiguity, particularly when using a short video for training.

Image Generation

StyleAdapter: A Single-Pass LoRA-Free Model for Stylized Image Generation

no code implementations4 Sep 2023 Zhouxia Wang, Xintao Wang, Liangbin Xie, Zhongang Qi, Ying Shan, Wenping Wang, Ping Luo

StyleAdapter can generate high-quality images that match the content of the prompts and adopt the style of the references (even for unseen styles) in a single pass, which is more flexible and efficient than previous methods.

Image Generation

Enhancing the vocal range of single-speaker singing voice synthesis with melody-unsupervised pre-training

no code implementations1 Sep 2023 Shaohuan Zhou, Xu Li, Zhiyong Wu, Ying Shan, Helen Meng

Specifically, in the pre-training step, we design a phoneme predictor to produce the frame-level phoneme probability vectors as the phonemic timing information and a speaker encoder to model the timbre variations of different singers, and directly estimate the frame-level f0 values from the audio to provide the pitch information.

Singing Voice Synthesis Unsupervised Pre-training

Exploring Model Transferability through the Lens of Potential Energy

1 code implementation ICCV 2023 Xiaotong Li, Zixuan Hu, Yixiao Ge, Ying Shan, Ling-Yu Duan

The experimental results on 10 downstream tasks and 12 self-supervised models demonstrate that our approach can seamlessly integrate into existing ranking techniques and enhance their performances, revealing its effectiveness for the model selection task and its potential for understanding the mechanism in transfer learning.

Model Selection Transfer Learning

Sparse3D: Distilling Multiview-Consistent Diffusion for Object Reconstruction from Sparse Views

no code implementations27 Aug 2023 Zi-Xin Zou, Weihao Cheng, Yan-Pei Cao, Shi-Sheng Huang, Ying Shan, Song-Hai Zhang

While recent techniques employ image diffusion models for generating plausible images at novel viewpoints or for distilling pre-trained diffusion priors into 3D representations using score distillation sampling (SDS), these methods often struggle to simultaneously achieve high-quality, consistent, and detailed results for both novel-view synthesis (NVS) and geometry.

3D Reconstruction Novel View Synthesis +1

Music Understanding LLaMA: Advancing Text-to-Music Generation with Question Answering and Captioning

1 code implementation22 Aug 2023 Shansong Liu, Atin Sakkeer Hussain, Chenshuo Sun, Ying Shan

To fill this gap, we present a methodology for generating question-answer pairs from existing audio captioning datasets and introduce the MusicQA Dataset designed for answering open-ended music-related questions.

Large Language Model Music Captioning +2

ViT-Lens: Towards Omni-modal Representations

1 code implementation20 Aug 2023 Weixian Lei, Yixiao Ge, Jianfeng Zhang, Dylan Sun, Kun Yi, Ying Shan, Mike Zheng Shou

A well-trained lens with a ViT backbone has the potential to serve as one of these foundation models, supervising the learning of subsequent modalities.

 Ranked #1 on Training-free 3D Point Cloud Classification on ModelNet40 (using extra training data)

3D Classification Question Answering +4

Guide3D: Create 3D Avatars from Text and Image Guidance

no code implementations18 Aug 2023 Yukang Cao, Yan-Pei Cao, Kai Han, Ying Shan, Kwan-Yee K. Wong

To this end, we introduce Guide3D, a zero-shot text-and-image-guided generative model for 3D avatar generation based on diffusion models.

Text to 3D

OmniZoomer: Learning to Move and Zoom in on Sphere at High-Resolution

no code implementations ICCV 2023 Zidong Cao, Hao Ai, Yan-Pei Cao, Ying Shan, XiaoHu Qie, Lin Wang

The M\"obius transformation is typically employed to further provide the opportunity for movement and zoom on ODIs, but applying it to the image level often results in blurry effect and aliasing problem.

SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension

1 code implementation30 Jul 2023 Bohao Li, Rui Wang, Guangzhi Wang, Yuying Ge, Yixiao Ge, Ying Shan

Based on powerful Large Language Models (LLMs), recent generative Multimodal Large Language Models (MLLMs) have gained prominence as a pivotal research area, exhibiting remarkable capability for both comprehension and generation.

Benchmarking Multiple-choice

GET3D--: Learning GET3D from Unconstrained Image Collections

no code implementations27 Jul 2023 Fanghua Yu, Xintao Wang, Zheyuan Li, Yan-Pei Cao, Ying Shan, Chao Dong

While generative models have shown potential in creating 3D textured shapes from 2D images, their applicability in 3D industries is limited due to the lack of a well-defined camera distribution in real-world scenarios, resulting in low-quality shapes.

Planting a SEED of Vision in Large Language Model

1 code implementation16 Jul 2023 Yuying Ge, Yixiao Ge, Ziyun Zeng, Xintao Wang, Ying Shan

Research on image tokenizers has previously reached an impasse, as frameworks employing quantized visual tokens have lost prominence due to subpar performance and convergence in multimodal comprehension (compared to BLIP-2, etc.)

Language Modelling Large Language Model

Neural Point-based Volumetric Avatar: Surface-guided Neural Points for Efficient and Photorealistic Volumetric Head Avatar

no code implementations11 Jul 2023 Cong Wang, Di Kang, Yan-Pei Cao, Linchao Bao, Ying Shan, Song-Hai Zhang

Rendering photorealistic and dynamically moving human heads is crucial for ensuring a pleasant and immersive experience in AR/VR and video conferencing applications.

NOFA: NeRF-based One-shot Facial Avatar Reconstruction

no code implementations7 Jul 2023 Wangbo Yu, Yanbo Fan, Yong Zhang, Xuan Wang, Fei Yin, Yunpeng Bai, Yan-Pei Cao, Ying Shan, Yang Wu, Zhongqian Sun, Baoyuan Wu

In this work, we propose a one-shot 3D facial avatar reconstruction framework that only requires a single source image to reconstruct a high-fidelity 3D facial avatar.

DragonDiffusion: Enabling Drag-style Manipulation on Diffusion Models

1 code implementation5 Jul 2023 Chong Mou, Xintao Wang, Jiechong Song, Ying Shan, Jian Zhang

Specifically, we construct classifier guidance based on the strong correspondence of intermediate features in the diffusion model.

DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models

1 code implementation5 Jul 2023 Liangbin Xie, Xintao Wang, Xiangyu Chen, Gen Li, Ying Shan, Jiantao Zhou, Chao Dong

After detecting the artifact regions, we develop a finetune procedure to improve GAN-based SR models with a few samples, so that they can deal with similar types of artifacts in more unseen real data.

Image Super-Resolution

ID-Pose: Sparse-view Camera Pose Estimation by Inverting Diffusion Models

no code implementations29 Jun 2023 Weihao Cheng, Yan-Pei Cao, Ying Shan

ID-Pose adds a noise to one image, and predicts the noise conditioned on the other image and a hypothesis of the relative pose.

Denoising Pose Estimation

DreamDiffusion: Generating High-Quality Images from Brain EEG Signals

1 code implementation29 Jun 2023 Yunpeng Bai, Xintao Wang, Yan-Pei Cao, Yixiao Ge, Chun Yuan, Ying Shan

This paper introduces DreamDiffusion, a novel method for generating high-quality images directly from brain electroencephalogram (EEG) signals, without the need to translate thoughts into text.

EEG Electroencephalogram (EEG) +1

DSRM: Boost Textual Adversarial Training with Distribution Shift Risk Minimization

1 code implementation27 Jun 2023 Songyang Gao, Shihan Dou, Yan Liu, Xiao Wang, Qi Zhang, Zhongyu Wei, Jin Ma, Ying Shan

Adversarial training is one of the best-performing methods in improving the robustness of deep language models.

On the Universal Adversarial Perturbations for Efficient Data-free Adversarial Detection

1 code implementation27 Jun 2023 Songyang Gao, Shihan Dou, Qi Zhang, Xuanjing Huang, Jin Ma, Ying Shan

Detecting adversarial samples that are carefully crafted to fool the model is a critical step to socially-secure applications.

text-classification Text Classification

PTVD: A Large-Scale Plot-Oriented Multimodal Dataset Based on Television Dramas

1 code implementation26 Jun 2023 Chen Li, Xutan Peng, Teng Wang, Yixiao Ge, Mengyang Liu, Xuyuan Xu, Yexin Wang, Ying Shan

Art forms such as movies and television (TV) dramas are reflections of the real world, which have attracted much attention from the multimodal learning community recently.

Genre classification Retrieval +1

Towards Unseen Triples: Effective Text-Image-joint Learning for Scene Graph Generation

no code implementations23 Jun 2023 Qianji Di, Wenxi Ma, Zhongang Qi, Tianxiang Hou, Ying Shan, Hanzi Wang

In this work, we propose a Text-Image-joint Scene Graph Generation (TISGG) model to resolve the unseen triples and improve the generalisation capability of the SGG models.

Graph Generation Scene Graph Generation +1

TaCA: Upgrading Your Visual Foundation Model with Task-agnostic Compatible Adapter

no code implementations22 Jun 2023 Binjie Zhang, Yixiao Ge, Xuyuan Xu, Ying Shan, Mike Zheng Shou

In situations involving system upgrades that require updating the upstream foundation model, it becomes essential to re-train all downstream modules to adapt to the new foundation model, which is inflexible and inefficient.

Question Answering Retrieval +5

SGAT4PASS: Spherical Geometry-Aware Transformer for PAnoramic Semantic Segmentation

1 code implementation6 Jun 2023 XueWei Li, Tao Wu, Zhongang Qi, Gaoang Wang, Ying Shan, Xi Li

Experimental results on Stanford2D3D Panoramic datasets show that SGAT4PASS significantly improves performance and robustness, with approximately a 2% increase in mIoU, and when small 3D disturbances occur in the data, the stability of our performance is improved by an order of magnitude.

Semantic Segmentation

Make-Your-Video: Customized Video Generation Using Textual and Structural Guidance

no code implementations1 Jun 2023 Jinbo Xing, Menghan Xia, Yuxin Liu, Yuechen Zhang, Yong Zhang, Yingqing He, Hanyuan Liu, Haoxin Chen, Xiaodong Cun, Xintao Wang, Ying Shan, Tien-Tsin Wong

Our method, dubbed Make-Your-Video, involves joint-conditional video generation using a Latent Diffusion Model that is pre-trained for still image synthesis and then promoted for video generation with the introduction of temporal modules.

Image Generation Video Generation

Inserting Anybody in Diffusion Models via Celeb Basis

1 code implementation1 Jun 2023 Ge Yuan, Xiaodong Cun, Yong Zhang, Maomao Li, Chenyang Qi, Xintao Wang, Ying Shan, Huicheng Zheng

Empowered by the proposed celeb basis, the new identity in our customized model showcases a better concept combination ability than previous personalization methods.

TaleCrafter: Interactive Story Visualization with Multiple Characters

1 code implementation29 May 2023 Yuan Gong, Youxin Pang, Xiaodong Cun, Menghan Xia, Yingqing He, Haoxin Chen, Longyue Wang, Yong Zhang, Xintao Wang, Ying Shan, Yujiu Yang

Accurate Story visualization requires several necessary elements, such as identity consistency across frames, the alignment between plain text and visual content, and a reasonable layout of objects in images.

Story Visualization

TVTSv2: Learning Out-of-the-box Spatiotemporal Visual Representations at Scale

1 code implementation23 May 2023 Ziyun Zeng, Yixiao Ge, Zhan Tong, Xihui Liu, Shu-Tao Xia, Ying Shan

We argue that tuning a text encoder end-to-end, as done in previous work, is suboptimal since it may overfit in terms of styles, thereby losing its original generalization ability to capture the semantics of various language registers.

Representation Learning

A Confidence-based Partial Label Learning Model for Crowd-Annotated Named Entity Recognition

1 code implementation21 May 2023 Limao Xiong, Jie zhou, Qunxi Zhu, Xiao Wang, Yuanbin Wu, Qi Zhang, Tao Gui, Xuanjing Huang, Jin Ma, Ying Shan

Particularly, we propose a Confidence-based Partial Label Learning (CPLL) method to integrate the prior confidence (given by annotators) and posterior confidences (learned by models) for crowd-annotated NER.

named-entity-recognition Named Entity Recognition +2

What Makes for Good Visual Tokenizers for Large Language Models?

1 code implementation20 May 2023 Guangzhi Wang, Yixiao Ge, Xiaohan Ding, Mohan Kankanhalli, Ying Shan

In our benchmark, which is curated to evaluate MLLMs visual semantic understanding and fine-grained perception capabilities, we discussed different visual tokenizers pre-trained with dominant methods (i. e., DeiT, CLIP, MAE, DINO), and observe that: i) Fully/weakly supervised models capture more semantics than self-supervised models, but the gap is narrowed by scaling up the pre-training dataset.

Image Captioning Object Counting +2

$π$-Tuning: Transferring Multimodal Foundation Models with Optimal Multi-task Interpolation

1 code implementation27 Apr 2023 Chengyue Wu, Teng Wang, Yixiao Ge, Zeyu Lu, Ruisong Zhou, Ying Shan, Ping Luo

Foundation models have achieved great advances in multi-task learning with a unified interface of unimodal and multimodal tasks.

Multi-Task Learning

HOSNeRF: Dynamic Human-Object-Scene Neural Radiance Fields from a Single Video

no code implementations ICCV 2023 Jia-Wei Liu, Yan-Pei Cao, Tianyuan Yang, Eric Zhongcong Xu, Jussi Keppo, Ying Shan, XiaoHu Qie, Mike Zheng Shou

Our method enables pausing the video at any frame and rendering all scene details (dynamic humans, objects, and backgrounds) from arbitrary viewpoints.

Human-Object Interaction Detection

NeAI: A Pre-convoluted Representation for Plug-and-Play Neural Ambient Illumination

no code implementations18 Apr 2023 Yiyu Zhuang, Qi Zhang, Xuan Wang, Hao Zhu, Ying Feng, Xiaoyu Li, Ying Shan, Xun Cao

Recent advances in implicit neural representation have demonstrated the ability to recover detailed geometry and material from multi-view images.

MasaCtrl: Tuning-Free Mutual Self-Attention Control for Consistent Image Synthesis and Editing

2 code implementations ICCV 2023 Mingdeng Cao, Xintao Wang, Zhongang Qi, Ying Shan, XiaoHu Qie, Yinqiang Zheng

Despite the success in large-scale text-to-image generation and text-conditioned image editing, existing methods still struggle to produce consistent generation and editing results.

Text-based Image Editing

Improved Test-Time Adaptation for Domain Generalization

1 code implementation CVPR 2023 Liang Chen, Yong Zhang, Yibing Song, Ying Shan, Lingqiao Liu

Generally, a TTT strategy hinges its performance on two main factors: selecting an appropriate auxiliary TTT task for updating and identifying reliable parameters to update during the test phase.

Domain Generalization Test

TagGPT: Large Language Models are Zero-shot Multimodal Taggers

1 code implementation6 Apr 2023 Chen Li, Yixiao Ge, Jiayong Mao, Dian Li, Ying Shan

Given a new entity that needs tagging for distribution, TagGPT introduces two alternative options for zero-shot tagging, i. e., a generative method with late semantic matching with the tag set, and another selective method with early matching in prompts.

Optical Character Recognition (OCR) Prompt Engineering +4

Learning Anchor Transformations for 3D Garment Animation

no code implementations CVPR 2023 Fang Zhao, Zekun Li, Shaoli Huang, Junwu Weng, Tianfei Zhou, Guo-Sen Xie, Jue Wang, Ying Shan

Once the anchor transformations are found, per-vertex nonlinear displacements of the garment template can be regressed in a canonical space, which reduces the complexity of deformation space learning.

DreamAvatar: Text-and-Shape Guided 3D Human Avatar Generation via Diffusion Models

1 code implementation3 Apr 2023 Yukang Cao, Yan-Pei Cao, Kai Han, Ying Shan, Kwan-Yee K. Wong

We present DreamAvatar, a text-and-shape guided framework for generating high-quality 3D human avatars with controllable poses.

Follow Your Pose: Pose-Guided Text-to-Video Generation using Pose-Free Videos

1 code implementation3 Apr 2023 Yue Ma, Yingqing He, Xiaodong Cun, Xintao Wang, Ying Shan, Xiu Li, Qifeng Chen

Generating text-editable and pose-controllable character videos have an imperious demand in creating various digital human.

Text-to-Video Generation Video Generation

DropMAE: Masked Autoencoders with Spatial-Attention Dropout for Tracking Tasks

1 code implementation CVPR 2023 Qiangqiang Wu, Tianyu Yang, Ziquan Liu, Baoyuan Wu, Ying Shan, Antoni B. Chan

However, we find that this simple baseline heavily relies on spatial cues while ignoring temporal relations for frame reconstruction, thus leading to sub-optimal temporal matching representations for VOT and VOS.

 Ranked #1 on Visual Object Tracking on TrackingNet (AUC metric)

Semantic Segmentation Video Object Segmentation +2

LayoutDiffusion: Controllable Diffusion Model for Layout-to-image Generation

1 code implementation CVPR 2023 Guangcong Zheng, Xianpan Zhou, XueWei Li, Zhongang Qi, Ying Shan, Xi Li

To overcome the difficult multimodal fusion of image and layout, we propose to construct a structural image patch with region information and transform the patched image into a special layout to fuse with the normal layout in a unified form.

Layout-to-Image Generation

VMesh: Hybrid Volume-Mesh Representation for Efficient View Synthesis

no code implementations28 Mar 2023 Yuan-Chen Guo, Yan-Pei Cao, Chen Wang, Yu He, Ying Shan, XiaoHu Qie, Song-Hai Zhang

With the emergence of neural radiance fields (NeRFs), view synthesis quality has reached an unprecedented level.

Accelerating Vision-Language Pretraining with Free Language Modeling

1 code implementation CVPR 2023 Teng Wang, Yixiao Ge, Feng Zheng, Ran Cheng, Ying Shan, XiaoHu Qie, Ping Luo

FLM successfully frees the prediction rate from the tie-up with the corruption rate while allowing the corruption spans to be customized for each token to be predicted.

Language Modelling Masked Language Modeling

BoPR: Body-aware Part Regressor for Human Shape and Pose Estimation

1 code implementation21 Mar 2023 Yongkang Cheng, Shaoli Huang, Jifeng Ning, Ying Shan

This paper presents a novel approach for estimating human body shape and pose from monocular images that effectively addresses the challenges of occlusions and depth ambiguity.

3D Human Pose Estimation Occlusion Handling

HRDFuse: Monocular 360°Depth Estimation by Collaboratively Learning Holistic-with-Regional Depth Distributions

no code implementations21 Mar 2023 Hao Ai, Zidong Cao, Yan-Pei Cao, Ying Shan, Lin Wang

Depth estimation from a monocular 360{\deg} image is a burgeoning problem owing to its holistic sensing of a scene.

Depth Estimation

Skinned Motion Retargeting with Residual Perception of Motion Semantics & Geometry

1 code implementation CVPR 2023 Jiaxu Zhang, Junwu Weng, Di Kang, Fang Zhao, Shaoli Huang, Xuefei Zhe, Linchao Bao, Ying Shan, Jue Wang, Zhigang Tu

Driven by our explored distance-based losses that explicitly model the motion semantics and geometry, these two modules can learn residual motion modifications on the source motion to generate plausible retargeted motion in a single inference without post-processing.

motion retargeting

Binary Embedding-based Retrieval at Tencent

1 code implementation17 Feb 2023 Yukang Gan, Yixiao Ge, Chang Zhou, Shupeng Su, Zhouchuan Xu, Xuyuan Xu, Quanchao Hui, Xiang Chen, Yexin Wang, Ying Shan

To tackle the challenge, we propose a binary embedding-based retrieval (BEBR) engine equipped with a recurrent binarization algorithm that enables customized bits per dimension.

Binarization Retrieval

T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models

2 code implementations16 Feb 2023 Chong Mou, Xintao Wang, Liangbin Xie, Yanze Wu, Jian Zhang, Zhongang Qi, Ying Shan, XiaoHu Qie

In this paper, we aim to ``dig out" the capabilities that T2I models have implicitly learned, and then explicitly use them to control the generation more granularly.

Image Generation Style Transfer

RILS: Masked Visual Reconstruction in Language Semantic Space

1 code implementation CVPR 2023 Shusheng Yang, Yixiao Ge, Kun Yi, Dian Li, Ying Shan, XiaoHu Qie, Xinggang Wang

Both masked image modeling (MIM) and natural language supervision have facilitated the progress of transferable visual pre-training.

DPE: Disentanglement of Pose and Expression for General Video Portrait Editing

1 code implementation CVPR 2023 Youxin Pang, Yong Zhang, Weize Quan, Yanbo Fan, Xiaodong Cun, Ying Shan, Dong-Ming Yan

In this paper, we introduce a novel self-supervised disentanglement framework to decouple pose and expression without 3DMMs and paired data, which consists of a motion editing module, a pose generator, and an expression generator.

Disentanglement Talking Face Generation +1

ViLEM: Visual-Language Error Modeling for Image-Text Retrieval

no code implementations CVPR 2023 Yuxin Chen, Zongyang Ma, Ziqi Zhang, Zhongang Qi, Chunfeng Yuan, Ying Shan, Bing Li, Weiming Hu, XiaoHu Qie, Jianping Wu

ViLEM then enforces the model to discriminate the correctness of each word in the plausible negative texts and further correct the wrong words via resorting to image information.

Contrastive Learning Retrieval +2

Mitigating Artifacts in Real-World Video Super-Resolution Models

1 code implementation14 Dec 2022 Liangbin Xie, Xintao Wang, Shuwei Shi, Jinjin Gu, Chao Dong, Ying Shan

To aggregate a new hidden state that contains fewer artifacts from the hidden state pool, we devise a Selective Cross Attention (SCA) module, in which the attention between input features and each hidden state is calculated.

Video Super-Resolution

Rethinking the Objectives of Vector-Quantized Tokenizers for Image Synthesis

no code implementations6 Dec 2022 YuChao Gu, Xintao Wang, Yixiao Ge, Ying Shan, XiaoHu Qie, Mike Zheng Shou

Vector-Quantized (VQ-based) generative models usually consist of two basic components, i. e., VQ tokenizers and generative transformers.

Conditional Image Generation

3D GAN Inversion with Facial Symmetry Prior

no code implementations CVPR 2023 Fei Yin, Yong Zhang, Xuan Wang, Tengfei Wang, Xiaoyu Li, Yuan Gong, Yanbo Fan, Xiaodong Cun, Ying Shan, Cengiz Oztireli, Yujiu Yang

It is natural to associate 3D GANs with GAN inversion methods to project a real image into the generator's latent space, allowing free-view consistent synthesis and editing, referred as 3D GAN inversion.

Image Reconstruction Neural Rendering

SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation

1 code implementation CVPR 2023 Wenxuan Zhang, Xiaodong Cun, Xuan Wang, Yong Zhang, Xi Shen, Yu Guo, Ying Shan, Fei Wang

We present SadTalker, which generates 3D motion coefficients (head pose, expression) of the 3DMM from audio and implicitly modulates a novel 3D-aware face render for talking head generation.

Image Animation Talking Head Generation

Local-to-Global Registration for Bundle-Adjusting Neural Radiance Fields

no code implementations CVPR 2023 Yue Chen, Xingyu Chen, Xuan Wang, Qi Zhang, Yu Guo, Ying Shan, Fei Wang

Neural Radiance Fields (NeRF) have achieved photorealistic novel views synthesis; however, the requirement of accurate camera poses limits its application.

Vis2Mus: Exploring Multimodal Representation Mapping for Controllable Music Generation

1 code implementation10 Nov 2022 Runbang Zhang, Yixiao Zhang, Kai Shao, Ying Shan, Gus Xia

In this study, we explore the representation mapping from the domain of visual arts to the domain of music, with which we can use visual arts as an effective handle to control music generation.

Music Generation Representation Learning +1

Darwinian Model Upgrades: Model Evolving with Selective Compatibility

no code implementations13 Oct 2022 Binjie Zhang, Shupeng Su, Yixiao Ge, Xuyuan Xu, Yexin Wang, Chun Yuan, Mike Zheng Shou, Ying Shan

The traditional model upgrading paradigm for retrieval requires recomputing all gallery embeddings before deploying the new model (dubbed as "backfilling"), which is quite expensive and time-consuming considering billions of instances in industrial applications.

Face Recognition Retrieval

Robust Human Matting via Semantic Guidance

1 code implementation11 Oct 2022 Xiangguang Chen, Ye Zhu, Yu Li, Bingtao Fu, Lei Sun, Ying Shan, Shan Liu

Unlike previous works, our framework is data efficient, which requires a small amount of matting ground-truth to learn to estimate high quality object mattes.

Image Matting Segmentation

MonoNeuralFusion: Online Monocular Neural 3D Reconstruction with Geometric Priors

no code implementations30 Sep 2022 Zi-Xin Zou, Shi-Sheng Huang, Yan-Pei Cao, Tai-Jiang Mu, Ying Shan, Hongbo Fu

This paper introduces a novel neural implicit scene representation with volume rendering for high-fidelity online 3D scene reconstruction from monocular videos.

3D Reconstruction 3D Scene Reconstruction

Music-driven Dance Regeneration with Controllable Key Pose Constraints

no code implementations8 Jul 2022 Junfu Pu, Ying Shan

The cross-modal transformer decoder achieves the capability of synthesizing smooth dance motion sequences, which keeps a consistency with key poses at corresponding positions, by introducing the local neighbor position embedding.

Motion Synthesis

Learning Music-Dance Representations through Explicit-Implicit Rhythm Synchronization

no code implementations7 Jul 2022 Jiashuo Yu, Junfu Pu, Ying Cheng, Rui Feng, Ying Shan

Although audio-visual representation has been proved to be applicable in many downstream tasks, the representation of dancing videos, which is more specific and always accompanied by music with complex auditory contents, remains challenging and uninvestigated.

Contrastive Learning Representation Learning +2

Not All Models Are Equal: Predicting Model Transferability in a Self-challenging Fisher Space

1 code implementation7 Jul 2022 Wenqi Shao, Xun Zhao, Yixiao Ge, Zhaoyang Zhang, Lei Yang, Xiaogang Wang, Ying Shan, Ping Luo

It is challenging because the ground-truth model ranking for each task can only be generated by fine-tuning the pre-trained models on the target dataset, which is brute-force and computationally expensive.

A Hierarchical Speaker Representation Framework for One-shot Singing Voice Conversion

no code implementations28 Jun 2022 Xu Li, Shansong Liu, Ying Shan

It is suspected that a single embedding vector may only capture averaged and coarse-grained speaker characteristics, which is insufficient for the SVC task.

Speaker Recognition Voice Conversion

AnimeSR: Learning Real-World Super-Resolution Models for Animation Videos

1 code implementation14 Jun 2022 Yanze Wu, Xintao Wang, Gen Li, Ying Shan

This paper studies the problem of real-world video super-resolution (VSR) for animation videos, and reveals three key improvements for practical animation VSR.

Video Super-Resolution

Do we really need temporal convolutions in action segmentation?

no code implementations26 May 2022 Dazhao Du, Bing Su, Yu Li, Zhongang Qi, Lingyu Si, Ying Shan

Most state-of-the-art methods focus on designing temporal convolution-based models, but the inflexibility of temporal convolutions and the difficulties in modeling long-term temporal dependencies restrict the potential of these models.

Action Classification Action Segmentation +1

Masked Image Modeling with Denoising Contrast

1 code implementation19 May 2022 Kun Yi, Yixiao Ge, Xiaotong Li, Shusheng Yang, Dian Li, Jianping Wu, Ying Shan, XiaoHu Qie

Since the development of self-supervised visual representation learning from contrastive learning to masked image modeling (MIM), there is no significant difference in essence, that is, how to design proper pretext tasks for vision dictionary look-up.

Contrastive Learning Denoising +6

VQFR: Blind Face Restoration with Vector-Quantized Dictionary and Parallel Decoder

1 code implementation13 May 2022 YuChao Gu, Xintao Wang, Liangbin Xie, Chao Dong, Gen Li, Ying Shan, Ming-Ming Cheng

Equipped with the VQ codebook as a facial detail dictionary and the parallel decoder design, the proposed VQFR can largely enhance the restored quality of facial details while keeping the fidelity to previous methods.

Blind Face Restoration Quantization

RepSR: Training Efficient VGG-style Super-Resolution Networks with Structural Re-Parameterization and Batch Normalization

no code implementations11 May 2022 Xintao Wang, Chao Dong, Ying Shan

Extensive experiments demonstrate that our simple RepSR is capable of achieving superior performance to previous SR re-parameterization methods among different model sizes.


Accelerating the Training of Video Super-Resolution Models

no code implementations10 May 2022 Lijian Lin, Xintao Wang, Zhongang Qi, Ying Shan

In this work, we show that it is possible to gradually train video models from small to large spatial/temporal sizes, i. e., in an easy-to-hard manner.

Video Super-Resolution

MM-RealSR: Metric Learning based Interactive Modulation for Real-World Super-Resolution

1 code implementation10 May 2022 Chong Mou, Yanze Wu, Xintao Wang, Chao Dong, Jian Zhang, Ying Shan

Instead of using known degradation levels as explicit supervision to the interactive mechanism, we propose a metric learning strategy to map the unquantifiable degradation levels in real-world scenarios to a metric space, which is trained in an unsupervised manner.

Image Restoration Metric Learning +1

Privacy-Preserving Model Upgrades with Bidirectional Compatible Training in Image Retrieval

1 code implementation29 Apr 2022 Shupeng Su, Binjie Zhang, Yixiao Ge, Xuyuan Xu, Yexin Wang, Chun Yuan, Ying Shan

The task of privacy-preserving model upgrades in image retrieval desires to reap the benefits of rapidly evolving new models without accessing the raw gallery images.

Image Retrieval Privacy Preserving +1

MILES: Visual BERT Pre-training with Injected Language Semantics for Video-text Retrieval

1 code implementation26 Apr 2022 Yuying Ge, Yixiao Ge, Xihui Liu, Alex Jinpeng Wang, Jianping Wu, Ying Shan, XiaoHu Qie, Ping Luo

Dominant pre-training work for video-text retrieval mainly adopt the "dual-encoder" architectures to enable efficient retrieval, where two separate encoders are used to contrast global video and text representations, but ignore detailed local semantics.

Action Recognition Retrieval +5

Temporally Efficient Vision Transformer for Video Instance Segmentation

3 code implementations CVPR 2022 Shusheng Yang, Xinggang Wang, Yu Li, Yuxin Fang, Jiemin Fang, Wenyu Liu, Xun Zhao, Ying Shan

To effectively and efficiently model the crucial temporal information within a video clip, we propose a Temporally Efficient Vision Transformer (TeViT) for video instance segmentation (VIS).

Instance Segmentation Semantic Segmentation +1

Unleashing Vanilla Vision Transformer with Masked Image Modeling for Object Detection

2 code implementations ICCV 2023 Yuxin Fang, Shusheng Yang, Shijie Wang, Yixiao Ge, Ying Shan, Xinggang Wang

We present an approach to efficiently and effectively adapt a masked image modeling (MIM) pre-trained vanilla Vision Transformer (ViT) for object detection, which is based on our two novel observations: (i) A MIM pre-trained vanilla ViT encoder can work surprisingly well in the challenging object-level recognition scenario even with randomly sampled partial observations, e. g., only 25% $\sim$ 50% of the input embeddings.

Instance Segmentation object-detection +1

CREATE: A Benchmark for Chinese Short Video Retrieval and Title Generation

no code implementations31 Mar 2022 Ziqi Zhang, Yuxin Chen, Zongyang Ma, Zhongang Qi, Chunfeng Yuan, Bing Li, Ying Shan, Weiming Hu

In this paper, we propose to CREATE, the first large-scale Chinese shoRt vidEo retrievAl and Title gEneration benchmark, to facilitate research and application in video titling and video retrieval in Chinese.

Retrieval Video Captioning +1

mc-BEiT: Multi-choice Discretization for Image BERT Pre-training

1 code implementation29 Mar 2022 Xiaotong Li, Yixiao Ge, Kun Yi, Zixuan Hu, Ying Shan, Ling-Yu Duan

Image BERT pre-training with masked image modeling (MIM) becomes a popular practice to cope with self-supervised representation learning.

Instance Segmentation object-detection +5

UMT: Unified Multi-modal Transformers for Joint Video Moment Retrieval and Highlight Detection

1 code implementation CVPR 2022 Ye Liu, Siyuan Li, Yang Wu, Chang Wen Chen, Ying Shan, XiaoHu Qie

Finding relevant moments and highlights in videos according to natural language queries is a natural and highly valuable common need in the current video content explosion era.

Highlight Detection Moment Retrieval +2

Revitalize Region Feature for Democratizing Video-Language Pre-training of Retrieval

2 code implementations15 Mar 2022 Guanyu Cai, Yixiao Ge, Binjie Zhang, Alex Jinpeng Wang, Rui Yan, Xudong Lin, Ying Shan, Lianghua He, XiaoHu Qie, Jianping Wu, Mike Zheng Shou

Recent dominant methods for video-language pre-training (VLP) learn transferable representations from the raw pixels in an end-to-end manner to achieve advanced performance on downstream video-language retrieval.

Question Answering Retrieval +4

All in One: Exploring Unified Video-Language Pre-training

1 code implementation CVPR 2023 Alex Jinpeng Wang, Yixiao Ge, Rui Yan, Yuying Ge, Xudong Lin, Guanyu Cai, Jianping Wu, Ying Shan, XiaoHu Qie, Mike Zheng Shou

In this work, we for the first time introduce an end-to-end video-language model, namely \textit{all-in-one Transformer}, that embeds raw video and textual signals into joint representations using a unified backbone architecture.

Ranked #6 on TGIF-Transition on TGIF-QA (using extra training data)

Language Modelling Multiple-choice +10

Towards Universal Backward-Compatible Representation Learning

2 code implementations3 Mar 2022 Binjie Zhang, Yixiao Ge, Yantao Shen, Shupeng Su, Fanzi Wu, Chun Yuan, Xuyuan Xu, Yexin Wang, Ying Shan

The task of backward-compatible representation learning is therefore introduced to support backfill-free model upgrades, where the new query features are interoperable with the old gallery features.

Face Recognition Representation Learning

Uncertainty Modeling for Out-of-Distribution Generalization

1 code implementation ICLR 2022 Xiaotong Li, Yongxing Dai, Yixiao Ge, Jun Liu, Ying Shan, Ling-Yu Duan

In this paper, we improve the network generalization ability by modeling the uncertainty of domain shifts with synthesized feature statistics during training.

Image Classification Out-of-Distribution Generalization +2

Hot-Refresh Model Upgrades with Regression-Alleviating Compatible Training in Image Retrieval

1 code implementation24 Jan 2022 Binjie Zhang, Yixiao Ge, Yantao Shen, Yu Li, Chun Yuan, Xuyuan Xu, Yexin Wang, Ying Shan

In contrast, hot-refresh model upgrades deploy the new model immediately and then gradually improve the retrieval accuracy by backfilling the gallery on-the-fly.

Image Retrieval regression +1

Bridging Video-text Retrieval with Multiple Choice Questions

2 code implementations CVPR 2022 Yuying Ge, Yixiao Ge, Xihui Liu, Dian Li, Ying Shan, XiaoHu Qie, Ping Luo

As an additional benefit, our method achieves competitive results with much shorter pre-training videos on single-modality downstream tasks, e. g., action recognition with linear evaluation.

Action Recognition Multiple-choice +8

BTS: A Bi-Lingual Benchmark for Text Segmentation in the Wild

no code implementations CVPR 2022 Xixi Xu, Zhongang Qi, jianqi ma, Honglun Zhang, Ying Shan, XiaoHu Qie

Current researches mainly focus on only English characters and digits, while few work studies Chinese characters due to the lack of public large-scale and high-quality Chinese datasets, which limits the practical application scenarios of text segmentation.

Segmentation Style Transfer +2

Object-aware Video-language Pre-training for Retrieval

1 code implementation CVPR 2022 Alex Jinpeng Wang, Yixiao Ge, Guanyu Cai, Rui Yan, Xudong Lin, Ying Shan, XiaoHu Qie, Mike Zheng Shou

In this work, we present Object-aware Transformers, an object-centric approach that extends video-language transformer to incorporate object representations.

Retrieval Text Matching

ACNet: Approaching-and-Centralizing Network for Zero-Shot Sketch-Based Image Retrieval

no code implementations24 Nov 2021 Hao Ren, Ziqiang Zheng, Yang Wu, Hong Lu, Yang Yang, Ying Shan, Sai-Kit Yeung

The huge domain gap between sketches and photos and the highly abstract sketch representations pose challenges for sketch-based image retrieval (\underline{SBIR}).

Retrieval Sketch-Based Image Retrieval

Hot-Refresh Model Upgrades with Regression-Free Compatible Training in Image Retrieval

no code implementations ICLR 2022 Binjie Zhang, Yixiao Ge, Yantao Shen, Yu Li, Chun Yuan, Xuyuan Xu, Yexin Wang, Ying Shan

In contrast, hot-refresh model upgrades deploy the new model immediately and then gradually improve the retrieval accuracy by backfilling the gallery on-the-fly.

Image Retrieval regression +1

Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution

1 code implementation NeurIPS 2021 Liangbin Xie, Xintao Wang, Chao Dong, Zhongang Qi, Ying Shan

Unlike previous integral gradient methods, our FAIG aims at finding the most discriminative filters instead of input pixels/features for degradation removal in blind SR networks.

Blind Super-Resolution Super-Resolution

Cross-modal Consensus Network for Weakly Supervised Temporal Action Localization

2 code implementations27 Jul 2021 Fa-Ting Hong, Jia-Chang Feng, Dan Xu, Ying Shan, Wei-Shi Zheng

In this work, we argue that the features extracted from the pretrained extractor, e. g., I3D, are not the WS-TALtask-specific features, thus the feature re-calibration is needed for reducing the task-irrelevant information redundancy.

Weakly Supervised Action Localization Weakly-supervised Temporal Action Localization +1

Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data

7 code implementations22 Jul 2021 Xintao Wang, Liangbin Xie, Chao Dong, Ying Shan

Though many attempts have been made in blind super-resolution to restore low-resolution images with unknown and complex degradations, they are still far from addressing general real-world degraded images.

Blind Super-Resolution Video Super-Resolution

Tracking Instances as Queries

1 code implementation22 Jun 2021 Shusheng Yang, Yuxin Fang, Xinggang Wang, Yu Li, Ying Shan, Bin Feng, Wenyu Liu

Recently, query based deep networks catch lots of attention owing to their end-to-end pipeline and competitive results on several fundamental computer vision tasks, such as object detection, semantic segmentation, and instance segmentation.

Instance Segmentation object-detection +4

Instances as Queries

4 code implementations ICCV 2021 Yuxin Fang, Shusheng Yang, Xinggang Wang, Yu Li, Chen Fang, Ying Shan, Bin Feng, Wenyu Liu

The key insight of QueryInst is to leverage the intrinsic one-to-one correspondence in object queries across different stages, as well as one-to-one correspondence between mask RoI features and object queries in the same stage.

Ranked #13 on Object Detection on COCO-O (using extra training data)

Instance Segmentation object-detection +3

Distilling Audio-Visual Knowledge by Compositional Contrastive Learning

1 code implementation CVPR 2021 Yanbei Chen, Yongqin Xian, A. Sophia Koepke, Ying Shan, Zeynep Akata

Having access to multi-modal cues (e. g. vision and audio) empowers some cognitive tasks to be done faster compared to learning from a single modality.

Audio Tagging audio-visual learning +5

Crossover Learning for Fast Online Video Instance Segmentation

1 code implementation ICCV 2021 Shusheng Yang, Yuxin Fang, Xinggang Wang, Yu Li, Chen Fang, Ying Shan, Bin Feng, Wenyu Liu

For temporal information modeling in VIS, we present a novel crossover learning scheme that uses the instance feature in the current frame to pixel-wisely localize the same instance in other frames.

Instance Segmentation Semantic Segmentation +2

Open-book Video Captioning with Retrieve-Copy-Generate Network

no code implementations CVPR 2021 Ziqi Zhang, Zhongang Qi, Chunfeng Yuan, Ying Shan, Bing Li, Ying Deng, Weiming Hu

Due to the rapid emergence of short videos and the requirement for content understanding and creation, the video captioning task has received increasing attention in recent years.

Retrieval Video Captioning

Towards Real-World Blind Face Restoration with Generative Facial Prior

1 code implementation CVPR 2021 Xintao Wang, Yu Li, Honglun Zhang, Ying Shan

Blind face restoration usually relies on facial priors, such as facial geometry prior or reference prior, to restore realistic and faithful details.

Blind Face Restoration Video Super-Resolution

Non-Inherent Feature Compatible Learning

no code implementations1 Jan 2021 Yantao Shen, Fanzi Wu, Ying Shan

In this work, we introduce an approach for feature compatible learning without inheriting old classifier and training data, i. e., Non-Inherent Feature Compatible Learning.


Detecting Interactions from Neural Networks via Topological Analysis

no code implementations NeurIPS 2020 Zirui Liu, Qingquan Song, Kaixiong Zhou, Ting-Hsiang Wang, Ying Shan, Xia Hu

Motivated by the observation, in this paper, we propose to investigate the interaction detection problem from a novel topological perspective by analyzing the connectivity in neural networks.

Towards Interaction Detection Using Topological Analysis on Neural Networks

no code implementations25 Oct 2020 Zirui Liu, Qingquan Song, Kaixiong Zhou, Ting Hsiang Wang, Ying Shan, Xia Hu

Detecting statistical interactions between input features is a crucial and challenging task.

A Simple Yet Effective Method for Video Temporal Grounding with Cross-Modality Attention

no code implementations23 Sep 2020 Binjie Zhang, Yu Li, Chun Yuan, Dejing Xu, Pin Jiang, Ying Shan

The task of language-guided video temporal grounding is to localize the particular video clip corresponding to a query sentence in an untrimmed video.

Dual Semantic Fusion Network for Video Object Detection

no code implementations16 Sep 2020 Lijian Lin, Haosheng Chen, Honglun Zhang, Jun Liang, Yu Li, Ying Shan, Hanzi Wang

Video object detection is a tough task due to the deteriorated quality of video sequences captured under complex environments.

object-detection Optical Flow Estimation +1

Recurrent Binary Embedding for GPU-Enabled Exhaustive Retrieval from Billion-Scale Semantic Vectors

no code implementations18 Feb 2018 Ying Shan, Jian Jiao, Jie Zhu, JC Mao

Building on top of the powerful concept of semantic learning, this paper proposes a Recurrent Binary Embedding (RBE) model that learns compact representations for real-time retrieval.

Information Retrieval Retrieval

Deep Embedding Forest: Forest-based Serving with Deep Embedding Features

no code implementations15 Mar 2017 Jie Zhu, Ying Shan, JC Mao, Dong Yu, Holakou Rahmanian, Yi Zhang

Built on top of a representative DNN model called Deep Crossing, and two forest/tree-based models including XGBoost and LightGBM, a two-step Deep Embedding Forest algorithm is demonstrated to achieve on-par or slightly better performance as compared with the DNN counterpart, with only a fraction of serving time on conventional hardware.

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