most citedModeling the Label Distributions for Weakly-Supervised Semantic Segmentation

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

SoccerNet 2026 Challenges Results

Anthony Cioppa, Silvio Giancola, Håkan Ardö +102

The SoccerNet 2026 Challenges constitute the sixth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision research in sports video underst…

cs.CV2026

Semantic-Aware, Physics-Informed, Geometry-Grounded Weather Video Synthesis

Chenghao Qian, Nedko Savov, Lingdong Kong +7

Weather synthesis aims to add weather effects to input videos while preserving scene identity, structure, and motion. The key limitation of existing methods is the lack of diversit…

cs.CV2024

Multi-Modality Driven LoRA for Adverse Condition Depth Estimation

Guanglei Yang, Rui Tian, Yongqiang Zhang +3

The autonomous driving community is increasingly focused on addressing corner case problems, particularly those related to ensuring driving safety under adverse conditions (e.g., n…

cs.CV2024

ChangeDiff: A Multi-Temporal Change Detection Data Generator with Flexible Text Prompts via Diffusion Model

Qi Zang, Jiayi Yang, Shuang Wang +3

Data-driven deep learning models have enabled tremendous progress in change detection (CD) with the support of pixel-level annotations. However, collecting diverse data and manuall…

eess.IV2024★ 1 cited

Modeling the Label Distributions for Weakly-Supervised Semantic Segmentation

Linshan Wu, Zhun Zhong, Jiayi Ma +4

Weakly-Supervised Semantic Segmentation (WSSS) aims to train segmentation models by weak labels, which is receiving significant attention due to its low annotation cost. Existing a…