1 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.CV2025★ 1 cited
UniTEX: Universal High Fidelity Generative Texturing for 3D Shapes
Yixun Liang, Kunming Luo, Xiao Chen +5
We present UniTEX, a novel two-stage 3D texture generation framework to create high-quality, consistent textures for 3D assets. Existing approaches predominantly rely on UV-based i…
cs.CV2025★ 1 cited
Step1X-3D: Towards High-Fidelity and Controllable Generation of Textured 3D Assets
Weiyu Li, Xuanyang Zhang, Zheng Sun +15
While generative artificial intelligence has advanced significantly across text, image, audio, and video domains, 3D generation remains comparatively underdeveloped due to fundamen…
cs.CV2024
Dora: Sampling and Benchmarking for 3D Shape Variational Auto-Encoders
Rui Chen, Jianfeng Zhang, Yixun Liang +7
Recent 3D content generation pipelines commonly employ Variational Autoencoders (VAEs) to encode shapes into compact latent representations for diffusion-based generation. However,…