3 citations · 6 across the 7 of their papers we have counts for
7 papers
Enhancing MMDiT-Based Text-to-Image Models for Similar Subject Generation
Tianyi Wei, Dongdong Chen, Yifan Zhou +1
Representing the cutting-edge technique of text-to-image models, the latest Multimodal Diffusion Transformer (MMDiT) largely mitigates many generation issues existing in previous m…
Learning Images Across Scales Using Adversarial Training
Krzysztof Wolski, Adarsh Djeacoumar, Alireza Javanmardi +7
The real world exhibits rich structure and detail across many scales of observation. It is difficult, however, to capture and represent a broad spectrum of scales using ordinary im…
MATLABER: Material-Aware Text-to-3D via LAtent BRDF auto-EncodeR
Xudong Xu, Zhaoyang Lyu, Xingang Pan +1
Based on powerful text-to-image diffusion models, text-to-3D generation has made significant progress in generating compelling geometry and appearance. However, existing methods st…
GVP: Generative Volumetric Primitives
Mallikarjun B R, Xingang Pan, Mohamed Elgharib +1
Advances in 3D-aware generative models have pushed the boundary of image synthesis with explicit camera control. To achieve high-resolution image synthesis, several attempts have b…
HQ3DAvatar: High Quality Controllable 3D Head Avatar
Kartik Teotia, Mallikarjun B R, Xingang Pan +4
Multi-view volumetric rendering techniques have recently shown great potential in modeling and synthesizing high-quality head avatars. A common approach to capture full head dynami…
Grid-guided Neural Radiance Fields for Large Urban Scenes
Linning Xu, Yuanbo Xiangli, Sida Peng +5
Purely MLP-based neural radiance fields (NeRF-based methods) often suffer from underfitting with blurred renderings on large-scale scenes due to limited model capacity. Recent appr…