most citedTask-Specific Context Decoupling for Object Detection

32 citations · 63 across the 7 of their papers we have counts for

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cs.CV20233 cited

Online Camera-to-ground Calibration for Autonomous Driving

Binbin Li, Xinyu Du, Yao Hu +2

Online camera-to-ground calibration is to generate a non-rigid body transformation between the camera and the road surface in a real-time manner. Existing solutions utilize static…

cs.CV20231 cited

Deep Graph-based Spatial Consistency for Robust Non-rigid Point Cloud Registration

Zheng Qin, Hao Yu, Changjian Wang +2

We study the problem of outlier correspondence pruning for non-rigid point cloud registration. In rigid registration, spatial consistency has been a commonly used criterion to disc…

cs.CV202332 cited

Task-Specific Context Decoupling for Object Detection

Jiayuan Zhuang, Zheng Qin, Hao Yu +1

Classification and localization are two main sub-tasks in object detection. Nonetheless, these two tasks have inconsistent preferences for feature context, i.e., localization expec…

cs.CV2022

1st Place Solution to ECCV 2022 Challenge on Out of Vocabulary Scene Text Understanding: End-to-End Recognition of Out of Vocabulary Words

Zhangzi Zhu, Chuhui Xue, Yu Hao +2

Scene text recognition has attracted increasing interest in recent years due to its wide range of applications in multilingual translation, autonomous driving, etc. In this report,…

cs.CV2022

Runner-Up Solution to ECCV 2022 Challenge on Out of Vocabulary Scene Text Understanding: Cropped Word Recognition

Zhangzi Zhu, Yu Hao, Wenqing Zhang +2

This report presents our 2nd place solution to ECCV 2022 challenge on Out-of-Vocabulary Scene Text Understanding (OOV-ST) : Cropped Word Recognition. This challenge is held in the…

cs.CV20223 cited

Training Vision Transformers with Only 2040 Images

Yun-Hao Cao, Hao Yu, Jianxin Wu

Vision Transformers (ViTs) is emerging as an alternative to convolutional neural networks (CNNs) for visual recognition. They achieve competitive results with CNNs but the lack of…