5 papers
Wat3R: Underwater 3D Geometry Learning without Annotations
Jiangwei Ren, Xingyu Jiang, Zijie Song +4
Estimating 3D geometry in underwater environments presents unique challenges due to light attenuation, scattering, and the absence of large-scale, high-quality 3D annotations. Pion…
More Than Generation: Unifying Generation and Depth Estimation via Text-to-Image Diffusion Models
Hongkai Lin, Dingkang Liang, Mingyang Du +2
Generative depth estimation methods leverage the rich visual priors stored in pre-trained text-to-image diffusion models, demonstrating astonishing zero-shot capability. However, p…
SoccerNet 2025 Challenges Results
Silvio Giancola, Anthony Cioppa, Marc Gutiérrez-Pérez +115
The SoccerNet 2025 Challenges mark the fifth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision research in football video understandi…
A Unified Image-Dense Annotation Generation Model for Underwater Scenes
Hongkai Lin, Dingkang Liang, Zhenghao Qi +1
Underwater dense prediction, especially depth estimation and semantic segmentation, is crucial for gaining a comprehensive understanding of underwater scenes. Nevertheless, high-qu…
Less is Enough: Training-Free Video Diffusion Acceleration via Runtime-Adaptive Caching
Xin Zhou, Dingkang Liang, Kaijin Chen +7
Video generation models have demonstrated remarkable performance, yet their broader adoption remains constrained by slow inference speeds and substantial computational costs, prima…