1 citations · 2 across the 3 of their papers we have counts for
4 papers
SceneMaker: Open-set 3D Scene Generation with Decoupled De-occlusion and Pose Estimation Model
Yukai Shi, Weiyu Li, Zihao Wang +4
We propose a decoupled 3D scene generation framework called SceneMaker in this work. Due to the lack of sufficient open-set de-occlusion and pose estimation priors, existing method…
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…
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…
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,…