7 papers
PhysRAG: Enhancing Physics-Awareness in Video Generation via Retrieval-Augmented Generation
Kexu Cheng, Zicheng Liu, Mingju Gao +2
Developing physically aware video generation models remains a significant challenge due to the difficulty in capturing diverse physical phenomena, such as thermal dynamics, mechani…
Conditional Text-to-Image Generation with Reference Guidance
Taewook Kim, Ze Wang, Zhengyuan Yang +4
Text-to-image diffusion models have demonstrated tremendous success in synthesizing visually stunning images given textual instructions. Despite remarkable progress in creating hig…
Tuning Timestep-Distilled Diffusion Model Using Pairwise Sample Optimization
Zichen Miao, Zhengyuan Yang, Kevin Lin +4
Recent advancements in timestep-distilled diffusion models have enabled high-quality image generation that rivals non-distilled multi-step models, but with significantly fewer infe…
MM-Vet v2: A Challenging Benchmark to Evaluate Large Multimodal Models for Integrated Capabilities
Weihao Yu, Zhengyuan Yang, Lingfeng Ren +7
MM-Vet, with open-ended vision-language questions targeting at evaluating integrated capabilities, has become one of the most popular benchmarks for large multimodal model evaluati…
AutoDirector: Online Auto-scheduling Agents for Multi-sensory Composition
Minheng Ni, Chenfei Wu, Huaying Yuan +6
With the advancement of generative models, the synthesis of different sensory elements such as music, visuals, and speech has achieved significant realism. However, the approach to…
Idea2Img: Iterative Self-Refinement with GPT-4V(ision) for Automatic Image Design and Generation
Zhengyuan Yang, Jianfeng Wang, Linjie Li +4
We introduce ``Idea to Image,'' a system that enables multimodal iterative self-refinement with GPT-4V(ision) for automatic image design and generation. Humans can quickly identify…