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20142024
most citedGPT-4V(ision) as a Generalist Evaluator for Vision-Language Tasks

13 citations · 52 across the 22 of their papers we have counts for

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6 papers · 1 filter

cs.CV20241 cited

TC-Bench: Benchmarking Temporal Compositionality in Text-to-Video and Image-to-Video Generation

Weixi Feng, Jiachen Li, Michael Saxon +3

Video generation has many unique challenges beyond those of image generation. The temporal dimension introduces extensive possible variations across frames, over which consistency…

cs.CV2024

Automatic Layout Planning for Visually-Rich Documents with Instruction-Following Models

Wanrong Zhu, Jennifer Healey, Ruiyi Zhang +2

Recent advancements in instruction-following models have made user interactions with models more user-friendly and efficient, broadening their applicability. In graphic design, non…

cs.CV2024

Ferret-v2: An Improved Baseline for Referring and Grounding with Large Language Models

Haotian Zhang, Haoxuan You, Philipp Dufter +8

While Ferret seamlessly integrates regional understanding into the Large Language Model (LLM) to facilitate its referring and grounding capability, it poses certain limitations: co…

cs.CV202313 cited

GPT-4V(ision) as a Generalist Evaluator for Vision-Language Tasks

Xinlu Zhang, Yujie Lu, Weizhi Wang +7

Automatically evaluating vision-language tasks is challenging, especially when it comes to reflecting human judgments due to limitations in accounting for fine-grained details. Alt…

cs.CV20231 cited

Learning Concise and Descriptive Attributes for Visual Recognition

An Yan, Yu Wang, Yiwu Zhong +6

Recent advances in foundation models present new opportunities for interpretable visual recognition -- one can first query Large Language Models (LLMs) to obtain a set of attribute…

cs.CV20238 cited

LLMScore: Unveiling the Power of Large Language Models in Text-to-Image Synthesis Evaluation

Yujie Lu, Xianjun Yang, Xiujun Li +2

Existing automatic evaluation on text-to-image synthesis can only provide an image-text matching score, without considering the object-level compositionality, which results in poor…