251 citations · 2.2k across the 123 of their papers we have counts for
124 papers
Weakly Supervised Semantic Segmentation for Large-Scale Point Cloud
Yachao Zhang, Zonghao Li, Yuan Xie +3
Existing methods for large-scale point cloud semantic segmentation require expensive, tedious and error-prone manual point-wise annotations. Intuitively, weakly supervised training…
Structured Two-stream Attention Network for Video Question Answering
Lianli Gao, Pengpeng Zeng, Jingkuan Song +4
To date, visual question answering (VQA) (i.e., image QA and video QA) is still a holy grail in vision and language understanding, especially for video QA. Compared with image QA t…
Part-level Action Parsing via a Pose-guided Coarse-to-Fine Framework
Xiaodong Chen, Xinchen Liu, Wu Liu +4
Action recognition from videos, i.e., classifying a video into one of the pre-defined action types, has been a popular topic in the communities of artificial intelligence, multimed…
Motion-Focused Contrastive Learning of Video Representations
Rui Li, Yiheng Zhang, Zhaofan Qiu +3
Motion, as the most distinct phenomenon in a video to involve the changes over time, has been unique and critical to the development of video representation learning. In this paper…
Representing Videos as Discriminative Sub-graphs for Action Recognition
Dong Li, Zhaofan Qiu, Yingwei Pan +3
Human actions are typically of combinatorial structures or patterns, i.e., subjects, objects, plus spatio-temporal interactions in between. Discovering such structures is therefore…
Uni-EDEN: Universal Encoder-Decoder Network by Multi-Granular Vision-Language Pre-training
Yehao Li, Jiahao Fan, Yingwei Pan +3
Vision-language pre-training has been an emerging and fast-developing research topic, which transfers multi-modal knowledge from rich-resource pre-training task to limited-resource…
Boosting Video Representation Learning with Multi-Faceted Integration
Zhaofan Qiu, Ting Yao, Chong-Wah Ngo +3
Video content is multifaceted, consisting of objects, scenes, interactions or actions. The existing datasets mostly label only one of the facets for model training, resulting in th…
Condensing a Sequence to One Informative Frame for Video Recognition
Zhaofan Qiu, Ting Yao, Yan Shu +2
Video is complex due to large variations in motion and rich content in fine-grained visual details. Abstracting useful information from such information-intensive media requires ex…
A Style and Semantic Memory Mechanism for Domain Generalization
Yang Chen, Yu Wang, Yingwei Pan +3
Mainstream state-of-the-art domain generalization algorithms tend to prioritize the assumption on semantic invariance across domains. Meanwhile, the inherent intra-domain style inv…
Transferrable Contrastive Learning for Visual Domain Adaptation
Yang Chen, Yingwei Pan, Yu Wang +3
Self-supervised learning (SSL) has recently become the favorite among feature learning methodologies. It is therefore appealing for domain adaptation approaches to consider incorpo…
CoCo-BERT: Improving Video-Language Pre-training with Contrastive Cross-modal Matching and Denoising
Jianjie Luo, Yehao Li, Yingwei Pan +3
BERT-type structure has led to the revolution of vision-language pre-training and the achievement of state-of-the-art results on numerous vision-language downstream tasks. Existing…
Dual Spoof Disentanglement Generation for Face Anti-spoofing with Depth Uncertainty Learning
Hangtong Wu, Dan Zen, Yibo Hu +2
Face anti-spoofing (FAS) plays a vital role in preventing face recognition systems from presentation attacks. Existing face anti-spoofing datasets lack diversity due to the insuffi…
Directional Self-supervised Learning for Heavy Image Augmentations
Yalong Bai, Yifan Yang, Wei Zhang +1
Despite the large augmentation family, only a few cherry-picked robust augmentation policies are beneficial to self-supervised image representation learning. In this paper, we prop…
ViDA-MAN: Visual Dialog with Digital Humans
Tong Shen, Jiawei Zuo, Fan Shi +7
We demonstrate ViDA-MAN, a digital-human agent for multi-modal interaction, which offers realtime audio-visual responses to instant speech inquiries. Compared to traditional text o…
A Baseline Framework for Part-level Action Parsing and Action Recognition
Xiaodong Chen, Xinchen Liu, Kun Liu +2
This technical report introduces our 2nd place solution to Kinetics-TPS Track on Part-level Action Parsing in ICCV DeeperAction Workshop 2021. Our entry is mainly based on YOLOF fo…
CoSeg: Cognitively Inspired Unsupervised Generic Event Segmentation
Xiao Wang, Jingen Liu, Tao Mei +1
Some cognitive research has discovered that humans accomplish event segmentation as a side effect of event anticipation. Inspired by this discovery, we propose a simple yet effecti…
Semi-Supervised Domain Generalizable Person Re-Identification
Lingxiao He, Wu Liu, Jian Liang +4
Existing person re-identification (re-id) methods are stuck when deployed to a new unseen scenario despite the success in cross-camera person matching. Recent efforts have been sub…
Deep Person Generation: A Survey from the Perspective of Face, Pose and Cloth Synthesis
Tong Sha, Wei Zhang, Tong Shen +2
Deep person generation has attracted extensive research attention due to its wide applications in virtual agents, video conferencing, online shopping and art/movie production. With…
Memory-Augmented Non-Local Attention for Video Super-Resolution
Jiyang Yu, Jingen Liu, Liefeng Bo +1
In this paper, we propose a novel video super-resolution method that aims at generating high-fidelity high-resolution (HR) videos from low-resolution (LR) ones. Previous methods pr…
X-modaler: A Versatile and High-performance Codebase for Cross-modal Analytics
Yehao Li, Yingwei Pan, Jingwen Chen +2
With the rise and development of deep learning over the past decade, there has been a steady momentum of innovation and breakthroughs that convincingly push the state-of-the-art of…
A Low Rank Promoting Prior for Unsupervised Contrastive Learning
Yu Wang, Jingyang Lin, Qi Cai +4
Unsupervised learning is just at a tipping point where it could really take off. Among these approaches, contrastive learning has seen tremendous progress and led to state-of-the-a…
Contextual Transformer Networks for Visual Recognition
Yehao Li, Ting Yao, Yingwei Pan +1
Transformer with self-attention has led to the revolutionizing of natural language processing field, and recently inspires the emergence of Transformer-style architecture design wi…
FasterPose: A Faster Simple Baseline for Human Pose Estimation
Hanbin Dai, Hailin Shi, Wu Liu +3
The performance of human pose estimation depends on the spatial accuracy of keypoint localization. Most existing methods pursue the spatial accuracy through learning the high-resol…
Augmentation Pathways Network for Visual Recognition
Yalong Bai, Mohan Zhou, Wei Zhang +2
Data augmentation is practically helpful for visual recognition, especially at the time of data scarcity. However, such success is only limited to quite a few light augmentations (…