665 citations · 1k across the 25 of their papers we have counts for
33 papers
Perceive, Interact, Predict: Learning Dynamic and Static Clues for End-to-End Motion Prediction
Bo Jiang, Shaoyu Chen, Xinggang Wang +7
Motion prediction is highly relevant to the perception of dynamic objects and static map elements in the scenarios of autonomous driving. In this work, we propose PIP, the first en…
Temporally Efficient Vision Transformer for Video Instance Segmentation
Shusheng Yang, Xinggang Wang, Yu Li +5
Recently vision transformer has achieved tremendous success on image-level visual recognition tasks. To effectively and efficiently model the crucial temporal information within a…
TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentation
Wenqiang Zhang, Zilong Huang, Guozhong Luo +5
Although vision transformers (ViTs) have achieved great success in computer vision, the heavy computational cost hampers their applications to dense prediction tasks such as semant…
Knowledge Mining with Scene Text for Fine-Grained Recognition
Hao Wang, Junchao Liao, Tianheng Cheng +5
Recently, the semantics of scene text has been proven to be essential in fine-grained image classification. However, the existing methods mainly exploit the literal meaning of scen…
AziNorm: Exploiting the Radial Symmetry of Point Cloud for Azimuth-Normalized 3D Perception
Shaoyu Chen, Xinggang Wang, Tianheng Cheng +4
Studying the inherent symmetry of data is of great importance in machine learning. Point cloud, the most important data format for 3D environmental perception, is naturally endowed…
Sparse Instance Activation for Real-Time Instance Segmentation
Tianheng Cheng, Xinggang Wang, Shaoyu Chen +5
In this paper, we propose a conceptually novel, efficient, and fully convolutional framework for real-time instance segmentation. Previously, most instance segmentation methods hea…