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20182023
most citedDual Semantic Fusion Network for Video Object Detection

29 citations · 44 across the 6 of their papers we have counts for

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9 papers · 1 filter

cs.CV20233 cited

Effective Whole-body Pose Estimation with Two-stages Distillation

Zhendong Yang, Ailing Zeng, Chun Yuan +1

Whole-body pose estimation localizes the human body, hand, face, and foot keypoints in an image. This task is challenging due to multi-scale body parts, fine-grained localization f…

cs.CV2023

FishDreamer: Towards Fisheye Semantic Completion via Unified Image Outpainting and Segmentation

Hao Shi, Yu Li, Kailun Yang +7

This paper raises the new task of Fisheye Semantic Completion (FSC), where dense texture, structure, and semantics of a fisheye image are inferred even beyond the sensor field-of-v…

cs.CV20221 cited

Learning Single Image Defocus Deblurring with Misaligned Training Pairs

Yu Li, Dongwei Ren, Xinya Shu +1

By adopting popular pixel-wise loss, existing methods for defocus deblurring heavily rely on well aligned training image pairs. Although training pairs of ground-truth and blurry i…

cs.CV20223 cited

Hot-Refresh Model Upgrades with Regression-Alleviating Compatible Training in Image Retrieval

Binjie Zhang, Yixiao Ge, Yantao Shen +5

The task of hot-refresh model upgrades of image retrieval systems plays an essential role in the industry but has never been investigated in academia before. Conventional cold-refr…

cs.CV20213 cited

Crossover Learning for Fast Online Video Instance Segmentation

Shusheng Yang, Yuxin Fang, Xinggang Wang +5

Modeling temporal visual context across frames is critical for video instance segmentation (VIS) and other video understanding tasks. In this paper, we propose a fast online VIS mo…

cs.CV20205 cited

Two-Stage Single Image Reflection Removal with Reflection-Aware Guidance

Yu Li, Ming Liu, Yaling Yi +3

Removing undesired reflection from an image captured through a glass surface is a very challenging problem with many practical application scenarios. For improving reflection remov…