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20242026
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cs.CV2026

Report of the 8th LSVOS Challenge: Complex and Multimodal Video Object Segmentation

Chang Liu, Henghui Ding, Lingyi Hong +36

This report summarizes the 8th Large-scale Video Object Segmentation (LSVOS) Challenge, held in conjunction with ECCV 2026. The challenge evaluates video segmentation in three comp…

cs.CV2026

Key-Frame Reasoning with SAM3: Third Place Solution for the MeViS-Text Track of the 8th LSVOS Challenge

Ce Bian, Xusheng He, Jinrong Zhang +3

This report presents a two-stage, training-free solution for the MeViS-Text track of the 8th LSVOS Challenge. The task requires a model to localize and segment the object specified…

cs.CV2026

VOS-Agent: The 1st Place Solution for the 8th LSVOS Challenge (MOSEv2 Track)

Canyang Wu, Jinrong Zhang, Xusheng He +3

Complex video object segmentation requires robust target propagation under severe occlusion, disappearance and reappearance. Although SAM3 provides strong promptable mask propagati…

cs.CV2026

Report of the 5th PVUW Challenge: Towards More Diverse Modalities in Pixel-Level Understanding

Chang Liu, Henghui Ding, Nikhila Ravi +40

This report summarizes the objectives, datasets, and top-performing methodologies of the 2026 Pixel-level Video Understanding in the Wild (PVUW) Challenge, hosted at CVPR 2026, whi…

cs.CV2026

The 1st Winner for 5th PVUW MeViS-Text Challenge: Strong MLLMs Meet SAM3 for Referring Video Object Segmentation

Xusheng He, Canyang Wu, Jinrong Zhang +3

This report presents our winning solution to the 5th PVUW MeViS-Text Challenge. The track studies referring video object segmentation under motion-centric language expressions, whe…

cs.CV2026

Advancing Complex Video Object Segmentation via Tracking-Enhanced Prompt: The 1st Winner for 5th PVUW MOSE Challenge

Jinrong Zhang, Canyang Wu, Xusheng He +3

In the Complex Video Object Segmentation task, researchers are required to track and segment specific targets within cluttered environments, which rigorously tests a method's capab…

cs.CV2025

TAPNext: Tracking Any Point (TAP) as Next Token Prediction

Artem Zholus, Carl Doersch, Yi Yang +7

Tracking Any Point (TAP) in a video is a challenging computer vision problem with many demonstrated applications in robotics, video editing, and 3D reconstruction. Existing methods…

cs.CV2024

TRecViT: A Recurrent Video Transformer

Viorica Pătrăucean, Xu Owen He, Joseph Heyward +10

We propose a novel block for \emph{causal} video modelling. It relies on a time-space-channel factorisation with dedicated blocks for each dimension: gated linear recurrent units (…