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cs.CV2026

Growing a Multi-head Twig via Distillation and Reinforcement Learning to Accelerate Large Vision-Language Models

Zhenwei Shao, Mingyang Wang, Weijun Zhang +6

Large vision-language models (VLMs) have demonstrated remarkable capabilities in open-world multimodal understanding, yet their high computational overheads pose great challenges f…

cs.CV2024

Prompting Video-Language Foundation Models with Domain-specific Fine-grained Heuristics for Video Question Answering

Ting Yu, Kunhao Fu, Shuhui Wang +2

Video Question Answering (VideoQA) represents a crucial intersection between video understanding and language processing, requiring both discriminative unimodal comprehension and s…

cs.CV2024

Multi-granularity Contrastive Cross-modal Collaborative Generation for End-to-End Long-term Video Question Answering

Ting Yu, Kunhao Fu, Jian Zhang +2

Long-term Video Question Answering (VideoQA) is a challenging vision-and-language bridging task focusing on semantic understanding of untrimmed long-term videos and diverse free-fo…

cs.CV2024

Learning to Discover Knowledge: A Weakly-Supervised Partial Domain Adaptation Approach

Mengcheng Lan, Min Meng, Jun Yu +1

Domain adaptation has shown appealing performance by leveraging knowledge from a source domain with rich annotations. However, for a specific target task, it is cumbersome to colle…

cs.CV2024

Boundary Discretization and Reliable Classification Network for Temporal Action Detection

Zhenying Fang, Jun Yu, Richang Hong

Temporal action detection aims to recognize the action category and determine each action instance's starting and ending time in untrimmed videos. The mixed methods have achieved r…