activity
20242026
collaborators

8 papers

cs.CV2026

EOVSAM: Efficient Open-Vocabulary Segmentation with SAM 3 in One Pass

Haomin Peng, Yongkang Li, Zhaoxiang Liu +4

Open-vocabulary segmentation identifies and segments objects from arbitrary textual descriptions. SAM 3 supports noun-phrase-guided segmentation and achieves competitive open-vocab…

cs.CV2026

FlowSeg: Dynamic Semantic Guidance for LLM-Conditioned Segmentation

Zekang Zhang, Guangyu Gao, Youyun Tang +7

LLM-conditioned segmentation has recently advanced rapidly by coupling large language models with iterative mask generation frameworks. However, we identify a persistent failure mo…

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.SD2026

Temporal Contrastive Decoding: A Training-Free Method for Large Audio-Language Models

Yanda Li, Yuhan Liu, Zirui Song +3

Large audio-language models (LALMs) generalize across speech, sound, and music, but unified decoders can exhibit a \emph{temporal smoothing bias}: transient acoustic cues may be un…

cs.CV2026

Rethinking MLLM Itself as a Segmenter with a Single Segmentation Token

Anqi Zhang, Xiaokang Ji, Guangyu Gao +3

Recent segmentation methods leveraging Multi-modal Large Language Models (MLLMs) have shown reliable object-level segmentation and enhanced spatial perception. However, almost all…

cs.CV2025

A Unified Reasoning Framework for Holistic Zero-Shot Video Anomaly Analysis

Dongheng Lin, Mengxue Qu, Kunyang Han +3

Most video-anomaly research stops at frame-wise detection, offering little insight into why an event is abnormal, typically outputting only frame-wise anomaly scores without spatia…