509 citations · 1.7k across the 38 of their papers we have counts for
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Generalized Focal Loss V2: Learning Reliable Localization Quality Estimation for Dense Object Detection
Xiang Li, Wenhai Wang, Xiaolin Hu +3
Localization Quality Estimation (LQE) is crucial and popular in the recent advancement of dense object detectors since it can provide accurate ranking scores that benefit the Non-M…
Generalized Focal Loss: Learning Qualified and Distributed Bounding Boxes for Dense Object Detection
Xiang Li, Wenhai Wang, Lijun Wu +5
One-stage detector basically formulates object detection as dense classification and localization. The classification is usually optimized by Focal Loss and the box location is com…
Generating Adjacency-Constrained Subgoals in Hierarchical Reinforcement Learning
Tianren Zhang, Shangqi Guo, Tian Tan +2
Goal-conditioned hierarchical reinforcement learning (HRL) is a promising approach for scaling up reinforcement learning (RL) techniques. However, it often suffers from training in…
Delving Deeper into the Decoder for Video Captioning
Haoran Chen, Jianmin Li, Xiaolin Hu
Video captioning is an advanced multi-modal task which aims to describe a video clip using a natural language sentence. The encoder-decoder framework is the most popular paradigm f…
End-to-End Face Parsing via Interlinked Convolutional Neural Networks
Zi Yin, Valentin Yiu, Xiaolin Hu +1
Face parsing is an important computer vision task that requires accurate pixel segmentation of facial parts (such as eyes, nose, mouth, etc.), providing a basis for further face an…
6D Object Pose Regression via Supervised Learning on Point Clouds
Ge Gao, Mikko Lauri, Yulong Wang +3
This paper addresses the task of estimating the 6 degrees of freedom pose of a known 3D object from depth information represented by a point cloud. Deep features learned by convolu…