most citedDVIS++: Improved Decoupled Framework for Universal Video Segmentation

3 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024★ 1 cited

SG-Adapter: Enhancing Text-to-Image Generation with Scene Graph Guidance

Guibao Shen, Luozhou Wang, Jiantao Lin +9

Recent advancements in text-to-image generation have been propelled by the development of diffusion models and multi-modality learning. However, since text is typically represented…

cs.CV2023★ 3 cited

DVIS++: Improved Decoupled Framework for Universal Video Segmentation

Tao Zhang, Xingye Tian, Yikang Zhou +7

We present the \textbf{D}ecoupled \textbf{VI}deo \textbf{S}egmentation (DVIS) framework, a novel approach for the challenging task of universal video segmentation, including video…

cs.CV2023★ 1 cited

Stable Segment Anything Model

Qi Fan, Xin Tao, Lei Ke +6

The Segment Anything Model (SAM) achieves remarkable promptable segmentation given high-quality prompts which, however, often require good skills to specify. To make SAM robust to…

cs.CV2023★ 1 cited

1st Place Solution for the 5th LSVOS Challenge: Video Instance Segmentation

Tao Zhang, Xingye Tian, Yikang Zhou +7

Video instance segmentation is a challenging task that serves as the cornerstone of numerous downstream applications, including video editing and autonomous driving. In this report…

cs.CV2023★ 2 cited

1st Place Solution for PVUW Challenge 2023: Video Panoptic Segmentation

Tao Zhang, Xingye Tian, Haoran Wei +6

Video panoptic segmentation is a challenging task that serves as the cornerstone of numerous downstream applications, including video editing and autonomous driving. We believe tha…