Summary of Vcbench: a Controllable Benchmark For Symbolic and Abstract Challenges in Video Cognition, by Chenglin Li and Qianglong Chen and Zhi Li and Feng Tao and Yin Zhang
VCBench: A Controllable Benchmark for Symbolic and Abstract Challenges in Video Cognition
by Chenglin Li, Qianglong Chen, Zhi Li, Feng Tao, Yin Zhang
First submitted to arxiv on: 14 Nov 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper introduces VCBench, a controllable benchmark designed to assess Large Video-Language Models’ (LVLMs) cognitive abilities. The existing benchmarks rely heavily on web-collected videos and human annotations or model-generated questions, which limit control over the video content and fall short in evaluating advanced cognitive abilities involving symbolic elements and abstract concepts. To address these limitations, VCBench generates video data using a Python-based engine, allowing for precise control over the video content. The benchmark features complex scenes and abstract concepts, paired with tailored question templates that target specific cognitive challenges. Even state-of-the-art models like Qwen2-VL-72B struggle with simple video cognition tasks involving abstract concepts, with performance dropping sharply as video complexity rises. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper makes a new tool to test how good computers are at understanding videos. Right now, we use websites to get videos and ask people or computers questions about them. But this is not very good because it’s hard to control what’s in the videos and it doesn’t help us understand if the computers can really think about complex things. The new tool, called VCBench, makes its own videos using a special computer program. It puts different things in the videos, like abstract ideas, and asks questions that are specific to those things. When we tested it with the best computers, they didn’t do very well with simple tasks that involve thinking about complex things. |
