5.3k citations · 12.2k across the 85 of their papers we have counts for
80 papers · 1 filter
Blind Image Super-Resolution: A Survey and Beyond
Anran Liu, Yihao Liu, Jinjin Gu +2
Blind image super-resolution (SR), aiming to super-resolve low-resolution images with unknown degradation, has attracted increasing attention due to its significance in promoting r…
MixStyle Neural Networks for Domain Generalization and Adaptation
Kaiyang Zhou, Yongxin Yang, Yu Qiao +1
Neural networks do not generalize well to unseen data with domain shifts -- a longstanding problem in machine learning and AI. To overcome the problem, we propose MixStyle, a simpl…
CT-Net: Channel Tensorization Network for Video Classification
Kunchang Li, Xianhang Li, Yali Wang +2
3D convolution is powerful for video classification but often computationally expensive, recent studies mainly focus on decomposing it on spatial-temporal and/or channel dimensions…
Refining Pseudo Labels with Clustering Consensus over Generations for Unsupervised Object Re-identification
Xiao Zhang, Yixiao Ge, Yu Qiao +1
Unsupervised object re-identification targets at learning discriminative representations for object retrieval without any annotations. Clustering-based methods conduct training wit…
Neighbourhood-guided Feature Reconstruction for Occluded Person Re-Identification
Shijie Yu, Dapeng Chen, Rui Zhao +2
Person images captured by surveillance cameras are often occluded by various obstacles, which lead to defective feature representation and harm person re-identification (Re-ID) per…
Multiple Domain Experts Collaborative Learning: Multi-Source Domain Generalization For Person Re-Identification
Shijie Yu, Feng Zhu, Dapeng Chen +5
Recent years have witnessed significant progress in person re-identification (ReID). However, current ReID approaches still suffer from considerable performance degradation when un…
Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentation
Hongbin Xu, Zhipeng Zhou, Yu Qiao +2
Recent studies have witnessed that self-supervised methods based on view synthesis obtain clear progress on multi-view stereo (MVS). However, existing methods rely on the assumptio…
Domain Generalization with MixStyle
Kaiyang Zhou, Yongxin Yang, Yu Qiao +1
Though convolutional neural networks (CNNs) have demonstrated remarkable ability in learning discriminative features, they often generalize poorly to unseen domains. Domain general…
Very Lightweight Photo Retouching Network with Conditional Sequential Modulation
Yihao Liu, Jingwen He, Xiangyu Chen +4
Photo retouching aims at improving the aesthetic visual quality of images that suffer from photographic defects, especially for poor contrast, over/under exposure, and inharmonious…
Affordance Transfer Learning for Human-Object Interaction Detection
Zhi Hou, Baosheng Yu, Yu Qiao +2
Reasoning the human-object interactions (HOI) is essential for deeper scene understanding, while object affordances (or functionalities) are of great importance for human to discov…
Detecting Human-Object Interaction via Fabricated Compositional Learning
Zhi Hou, Baosheng Yu, Yu Qiao +2
Human-Object Interaction (HOI) detection, inferring the relationships between human and objects from images/videos, is a fundamental task for high-level scene understanding. Howeve…
Temporal Context Aggregation Network for Temporal Action Proposal Refinement
Zhiwu Qing, Haisheng Su, Weihao Gan +7
Temporal action proposal generation aims to estimate temporal intervals of actions in untrimmed videos, which is a challenging yet important task in the video understanding field.…
PC-HMR: Pose Calibration for 3D Human Mesh Recovery from 2D Images/Videos
Tianyu Luan, Yali Wang, Junhao Zhang +3
The end-to-end Human Mesh Recovery (HMR) approach has been successfully used for 3D body reconstruction. However, most HMR-based frameworks reconstruct human body by directly learn…
Unsupervised Person Re-Identification with Multi-Label Learning Guided Self-Paced Clustering
Qing Li, Xiaojiang Peng, Yu Qiao +1
Although unsupervised person re-identification (Re-ID) has drawn increasing research attention recently, it remains challenging to learn discriminative features without annotations…
ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic
Xiangtao Kong, Hengyuan Zhao, Yu Qiao +1
We aim at accelerating super-resolution (SR) networks on large images (2K-8K). The large images are usually decomposed into small sub-images in practical usages. Based on this proc…
Investigate Indistinguishable Points in Semantic Segmentation of 3D Point Cloud
Mingye Xu, Zhipeng Zhou, Junhao Zhang +1
This paper investigates the indistinguishable points (difficult to predict label) in semantic segmentation for large-scale 3D point clouds. The indistinguishable points consist of…
Exploring Emotion Features and Fusion Strategies for Audio-Video Emotion Recognition
Hengshun Zhou, Debin Meng, Yuanyuan Zhang +4
The audio-video based emotion recognition aims to classify a given video into basic emotions. In this paper, we describe our approaches in EmotiW 2019, which mainly explores emotio…
Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point Cloud
Mutian Xu, Junhao Zhang, Zhipeng Zhou +3
In 2D image processing, some attempts decompose images into high and low frequency components for describing edge and smooth parts respectively. Similarly, the contour and flat are…
Visual Compositional Learning for Human-Object Interaction Detection
Zhi Hou, Xiaojiang Peng, Yu Qiao +1
Human-Object interaction (HOI) detection aims to localize and infer relationships between human and objects in an image. It is challenging because an enormous number of possible co…
SmallBigNet: Integrating Core and Contextual Views for Video Classification
Xianhang Li, Yali Wang, Zhipeng Zhou +1
Temporal convolution has been widely used for video classification. However, it is performed on spatio-temporal contexts in a limited view, which often weakens its capacity of lear…
COCAS: A Large-Scale Clothes Changing Person Dataset for Re-identification
Shijie Yu, Shihua Li, Dapeng Chen +3
Recent years have witnessed great progress in person re-identification (re-id). Several academic benchmarks such as Market1501, CUHK03 and DukeMTMC play important roles to promote…
Learning to Predict Context-adaptive Convolution for Semantic Segmentation
Jianbo Liu, Junjun He, Jimmy S. Ren +2
Long-range contextual information is essential for achieving high-performance semantic segmentation. Previous feature re-weighting methods demonstrate that using global context for…
Context-Transformer: Tackling Object Confusion for Few-Shot Detection
Ze Yang, Yali Wang, Xianyu Chen +2
Few-shot object detection is a challenging but realistic scenario, where only a few annotated training images are available for training detectors. A popular approach to handle thi…
TTPP: Temporal Transformer with Progressive Prediction for Efficient Action Anticipation
Wen Wang, Xiaojiang Peng, Yanzhou Su +2
Video action anticipation aims to predict future action categories from observed frames. Current state-of-the-art approaches mainly resort to recurrent neural networks to encode hi…