3 papers
cs.CL2025
UniHetero: Could Generation Enhance Understanding for Vision-Language-Model at Large Data Scale?
Fengjiao Chen, Minhao Jing, Weitao Lu +3
Vision-language large models are moving toward the unification of visual understanding and visual generation tasks. However, whether generation can enhance understanding is still u…
cs.CV2025
EvalTalker: Learning to Evaluate Real-Portrait-Driven Multi-Subject Talking Humans
Yingjie Zhou, Xilei Zhu, Siyu Ren +11
Speech-driven Talking Human (TH) generation, commonly known as "Talker," currently faces limitations in multi-subject driving capabilities. Extending this paradigm to "Multi-Talker…
cs.CV2025
Q-REAL: Towards Realism and Plausibility Evaluation for AI-Generated Content
Shushi Wang, Zicheng Zhang, Chunyi Li +7
Quality assessment of AI-generated content is crucial for evaluating model capability and guiding model optimization. However, most existing quality assessment datasets and models…