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cs.CV2026
VI-Bench: Benchmarking Prompt Inversion from AIGC Videos
Wulin Xie, Rui Zhao, Kecen Li +5
Recent advances in video generation have made prompt-based control increasingly central to AIGC video generation. Prompts specify what a video should depict and how it should be re…
cs.CV2025
MME-VideoOCR: Evaluating OCR-Based Capabilities of Multimodal LLMs in Video Scenarios
Yang Shi, Huanqian Wang, Wulin Xie +20
Multimodal Large Language Models (MLLMs) have achieved considerable accuracy in Optical Character Recognition (OCR) from static images. However, their efficacy in video OCR is sign…
cs.CV2025
MME-Unify: A Comprehensive Benchmark for Unified Multimodal Understanding and Generation Models
Wulin Xie, Yi-Fan Zhang, Chaoyou Fu +6
Existing MLLM benchmarks face significant challenges in evaluating Unified MLLMs (U-MLLMs) due to: 1) lack of standardized benchmarks for traditional tasks, leading to inconsistent…