Dimensions overall score 8.0

• TrajSeg outperforms all existing video reasoning segmentation methods on all metricsresult 90%
• Bidirectional text-trajectory alignment enhances correspondence and improves object trajectory perception in videosmethod 85%
• The unified mask decoder enables end-to-end trainable framework simplificationtechnical 80%
• Previous methods struggle with trajectory perception when faced with severe video dynamicslimitation 85%
• The frame-level content integration module adapts MLLM-parsed trajectory-level tokens to frame-specific informationtechnical 85%
• Scalability might be an issue due to computational demandslimitation 70%
• Performance might degrade in extremely complex or noisy environments beyond tested datasetslimitation 65%
• TrajSeg demonstrates robustness and efficiency across video reasoning segmentation benchmarksresult 80%

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