activity
20242026
most citedEvaluating SAM2 for Video Semantic Segmentation

1 citations · 1 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2026

STAC: Selective Spatiotemporal Aggregation and Compression for Video Reasoning Segmentation

Syed Ariff Syed Hesham, Yun Liu, Guolei Sun +4

Video reasoning segmentation demands pixel-accurate object tracking across hundreds of frames under complex natural language queries, producing dense spatiotemporal tokens whose qu…

cs.CV2025★ 1 cited

Evaluating SAM2 for Video Semantic Segmentation

Syed Hesham Syed Ariff, Yun Liu, Guolei Sun +4

The Segmentation Anything Model 2 (SAM2) has proven to be a powerful foundation model for promptable visual object segmentation in both images and videos, capable of storing object…

cs.CV2025

A Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects

Guohuan Xie, Syed Ariff Syed Hesham, Wenya Guo +4

Video Scene Parsing (VSP) studies dense video understanding, where every pixel in each frame must be segmented, each region must be named, and each object identity must remain cohe…

eess.IV2025

Exploiting Temporal State Space Sharing for Video Semantic Segmentation

Syed Ariff Syed Hesham, Yun Liu, Guolei Sun +5

Video semantic segmentation (VSS) plays a vital role in understanding the temporal evolution of scenes. Traditional methods often segment videos frame-by-frame or in a short tempor…

cs.CV2025

Generalized Few-shot 3D Point Cloud Segmentation with Vision-Language Model

Zhaochong An, Guolei Sun, Yun Liu +4

Generalized few-shot 3D point cloud segmentation (GFS-PCS) adapts models to new classes with few support samples while retaining base class segmentation. Existing GFS-PCS methods e…

cs.MM2024

Towards Open-Vocabulary Video Semantic Segmentation

Xinhao Li, Yun Liu, Guolei Sun +3

Semantic segmentation in videos has been a focal point of recent research. However, existing models encounter challenges when faced with unfamiliar categories. To address this, we…

cs.CV2024

Multimodality Helps Few-shot 3D Point Cloud Semantic Segmentation

Zhaochong An, Guolei Sun, Yun Liu +5

Few-shot 3D point cloud segmentation (FS-PCS) aims at generalizing models to segment novel categories with minimal annotated support samples. While existing FS-PCS methods have sho…

cs.CV2024

Rethinking Few-shot 3D Point Cloud Semantic Segmentation

Zhaochong An, Guolei Sun, Yun Liu +5

This paper revisits few-shot 3D point cloud semantic segmentation (FS-PCS), with a focus on two significant issues in the state-of-the-art: foreground leakage and sparse point dist…