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cs.CV2026
Unified Spatiotemporal Token Compression for Video-LLMs at Ultra-Low Retention
Junhao Du, Jialong Xue, Anqi Li +2
Video large language models (Video-LLMs) face high computational costs due to large volumes of visual tokens. Existing token compression methods typically adopt a two-stage spatiot…
cs.CV2026
VSD-MOT: End-to-End Multi-Object Tracking in Low-Quality Video Scenes Guided by Visual Semantic Distillation
Jun Du
Existing multi-object tracking algorithms typically fail to adequately address the issues in low-quality videos, resulting in a significant decline in tracking performance when ima…
cs.CV2026
EARTalking: End-to-end GPT-style Autoregressive Talking Head Synthesis with Frame-wise Control
Yuzhe Weng, Haotian Wang, Yuanhong Yu +4
Audio-driven talking head generation aims to create vivid and realistic videos from a static portrait and speech. Existing AR-based methods rely on intermediate facial representati…