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VFIG: Vectorizing Complex Figures in SVG with Vision-Language Models
VLMs for high-fidelity raster-to-SVG with VFIG-Data, curriculum SFT+RL, and VFIG-Bench
Qijia He, Xunmei Liu, Hammaad Memon, Ziang Li, Zixian Ma, Jaemin Cho, Jason Ren, Daniel S Weld, Ranjay Krishna
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V-Co: A Closer Look at Visual Representation Alignment via Co-Denoising
A systematic study of visual co-denoising for representation-aligned pixel-space diffusion
Han Lin, Xichen Pan, Zun Wang, Yue Zhang, Chu Wang, Jaemin Cho, Mohit Bansal
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InfinityStory: Unlimited Video Generation with World Consistency and Character-Aware Shot Transitions
Long-form video generation with world consistency, multi-subject shot transitions, and a 10K transition dataset
Mohamed Elmoghany, Liangbing Zhao, Xiaoqian Shen, Subhojyoti Mukherjee, Yang Zhou, Gang Wu, Viet Dac Lai, Seunghyun Yoon, Ryan Rossi, Abdullah Rashwan, Puneet Mathur, Varun Manjunatha, Daksh Dangi, Chien Nguyen, Nedim Lipka, Trung Bui, Krishna Kumar Singh, Ruiyi Zhang, Xiaolei Huang, Jaemin Cho, Yu Wang, Namyong Park, Zhengzhong Tu, Hongjie Chen, Hoda Eldardiry, Nesreen Ahmed, Thien Nguyen, Dinesh Manocha, Mohamed Elhoseiny, Franck Dernoncourt
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AnchorWeave: World-Consistent Video Generation with Retrieved Local Spatial Memories
Camera-controllable video generation with retrieved local geometric memories instead of a single global 3D reconstruction
Zun Wang, Han Lin, Jaehong Yoon, Jaemin Cho, Yue Zhang, Mohit Bansal
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A Survey on Long-Video Storytelling Generation: Architectures, Consistency, and Cinematic Quality
a survey on long-video storytelling generation
Mohamed Elmoghany, Ryan Rossi, Seunghyun Yoon, Subhojyoti Mukherjee, Eslam Bakr, Puneet Mathur, Gang Wu, Viet Dac Lai, Nedim Lipka, Ruiyi Zhang, Varun Manjunatha, Chien Nguyen, Daksh Dangi, Abel Salinas, Mohammad Taesiri, Hongjie Chen, Xiaolei Huang, Joe Barrow, Nesreen Ahmed, Hoda Eldardiry, Namyong Park, Yu Wang, Jaemin Cho, Anh Totti Nguyen, Zhengzhong Tu, Thien Nguyen, Dinesh Manocha, Mohamed Elhoseiny, Franck Dernoncourt
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Executable Functional Abstractions: Inferring Generative Programs for Advanced Math Problems
EFA is a new way to generate diverse math problems for LLMs, by inferring generative programs from seed problems
Zaid Khan, Elias Stengel-Eskin, Archiki Prasad, Jaemin Cho, Mohit Bansal
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Executable Functional Abstractions: Inferring Generative Programs for Advanced Math Problems
Training-free Guidance in Text-to-Video Generation via Multimodal Planning and Structured Noise Initialization
Video sketch as a new training-free guidance method for T2V diffusion models
Jialu Li*, Shoubin Yu*, Han Lin*, Jaemin Cho, Jaehong Yoon, Mohit Bansal
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Training-free Guidance in Text-to-Video Generation via Multimodal Planning and Structured Noise Initialization