PercepCap framework enhances video captioning by making perception explicit

Researchers have introduced PercepCap, a novel framework for video captioning that explicitly models spatio-temporal perception before generating descriptions. This approach aims to improve accuracy by making the underlying perceptual evidence, such as object trajectories and temporal events, visible. PercepCap utilizes a two-stage training strategy, including supervised fine-tuning and reinforcement learning, to optimize both the perception trace and the final caption. The framework has demonstrated superior performance over the Qwen3-VL baseline in evaluations. AI

IMPACT This framework could improve the interpretability and accuracy of AI models generating descriptions from video content.

RANK_REASON This is a research paper detailing a new framework for video captioning. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

• PercepCap
• Qwen3 VL

• paper
• model release

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