1 citations · 1 across the 13 of their papers we have counts for
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GANFusion: Feed-Forward Text-to-3D with Diffusion in GAN Space
Souhaib Attaiki, Paul Guerrero, Duygu Ceylan +2
We train a feed-forward text-to-3D diffusion generator for human characters using only single-view 2D data for supervision. Existing 3D generative models cannot yet match the fidel…
Track4Gen: Teaching Video Diffusion Models to Track Points Improves Video Generation
Hyeonho Jeong, Chun-Hao Paul Huang, Jong Chul Ye +2
While recent foundational video generators produce visually rich output, they still struggle with appearance drift, where objects gradually degrade or change inconsistently across…
Motion Modes: What Could Happen Next?
Karran Pandey, Matheus Gadelha, Yannick Hold-Geoffroy +3
Predicting diverse object motions from a single static image remains challenging, as current video generation models often entangle object movement with camera motion and other sce…
SuperGaussian: Repurposing Video Models for 3D Super Resolution
Yuan Shen, Duygu Ceylan, Paul Guerrero +4
We present a simple, modular, and generic method that upsamples coarse 3D models by adding geometric and appearance details. While generative 3D models now exist, they do not yet m…