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20202026
most citedGeoSegNet: Point Cloud Semantic Segmentation via Geometric Encoder-Decoder Modeling

25 citations · 85 across the 15 of their papers we have counts for

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11 papers · 1 filter

cs.CV2025

AlignFreeNet: Is Cross-Modal Pre-Alignment Necessary? An End-to-End Alignment-Free Lightweight Network for Visible-Infrared Object Detection

Dingkun Zhu, Haote Zhang, Lipeng Gu +7

Cross-modal misalignments, such as spatial offsets, resolution discrepancies, and semantic deficiencies, frequently occur in visible-infrared object detection (VI-OD). To mitigate…

cs.CV2024

FriendNet: Detection-Friendly Dehazing Network

Yihua Fan, Yongzhen Wang, Mingqiang Wei +2

Adverse weather conditions often impair the quality of captured images, inevitably inducing cutting-edge object detection models for advanced driver assistance systems (ADAS) and a…

cs.CV2023★ 9 cited

Rethinking Real-world Image Deraining via An Unpaired Degradation-Conditioned Diffusion Model

Yiyang Shen, Mingqiang Wei, Yongzhen Wang +2

Recent diffusion models have exhibited great potential in generative modeling tasks. Part of their success can be attributed to the ability of training stable on huge sets of paire…

cs.CV2022★ 1 cited

SPCNet: Stepwise Point Cloud Completion Network

Fei Hu, Honghua Chen, Xuequan Lu +5

How will you repair a physical object with large missings? You may first recover its global yet coarse shape and stepwise increase its local details. We are motivated to imitate th…

cs.CV2022

TogetherNet: Bridging Image Restoration and Object Detection Together via Dynamic Enhancement Learning

Yongzhen Wang, Xuefeng Yan, Kaiwen Zhang +4

Adverse weather conditions such as haze, rain, and snow often impair the quality of captured images, causing detection networks trained on normal images to generalize poorly in the…

cs.CV2022

Contrastive Semantic-Guided Image Smoothing Network

Jie Wang, Yongzhen Wang, Yidan Feng +5

Image smoothing is a fundamental low-level vision task that aims to preserve salient structures of an image while removing insignificant details. Deep learning has been explored in…