3 citations · 5 across the 6 of their papers we have counts for
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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…
MLLM-Assisted Audio VOS: A 3rd Place Report for the MeViS-Audio Track, 8th LSVOS Challenge
Liangtao Shi, Jinxia Xie, Xiantao Hu +1
In this technical report, we present a training-free framework for audio-guided video object segmentation, which integrates Multimodal Large Language Models (MLLMs) with SAM-based…
Explicit Context Reasoning with Supervision for Visual Tracking
Fansheng Zeng, Bineng Zhong, Haiying Xia +4
Contextual reasoning with constraints is crucial for enhancing temporal consistency in cross-frame modeling for visual tracking. However, mainstream tracking algorithms typically a…
Adaptive Perception for Unified Visual Multi-modal Object Tracking
Xiantao Hu, Bineng Zhong, Qihua Liang +4
Recently, many multi-modal trackers prioritize RGB as the dominant modality, treating other modalities as auxiliary, and fine-tuning separately various multi-modal tasks. This imba…
Autoregressive Queries for Adaptive Tracking with Spatio-TemporalTransformers
Jinxia Xie, Bineng Zhong, Zhiyi Mo +4
The rich spatio-temporal information is crucial to capture the complicated target appearance variations in visual tracking. However, most top-performing tracking algorithms rely on…
Explicit Visual Prompts for Visual Object Tracking
Liangtao Shi, Bineng Zhong, Qihua Liang +3
How to effectively exploit spatio-temporal information is crucial to capture target appearance changes in visual tracking. However, most deep learning-based trackers mainly focus o…