1 citations · 1 across the 8 of their papers we have counts for
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Quartet of Diffusions: Structure-Aware Point Cloud Generation through Part and Symmetry Guidance
Chenliang Zhou, Fangcheng Zhong, Weihao Xia +3
We introduce the Quartet of Diffusions, a structure-aware point cloud generation framework that explicitly models part composition and symmetry. Unlike prior methods that treat sha…
Self-Supervised Implicit Attention Priors for Point Cloud Reconstruction
Kyle Fogarty, Chenyue Cai, Jing Yang +2
Recovering high-quality surfaces from irregular point cloud is ill-posed unless strong geometric priors are available. We introduce an implicit self-prior approach that distills a…
Twist and Compute: The Cost of Pose in 3D Generative Diffusion
Kyle Fogarty, Jack Foster, Boqiao Zhang +2
Despite their impressive results, large-scale image-to-3D generative models remain opaque in their inductive biases. We identify a significant limitation in image-conditioned 3D ge…
Best Foot Forward: Robust Foot Reconstruction in-the-wild
Kyle Fogarty, Jing Yang, Chayan Kumar Patodi +5
Accurate 3D foot reconstruction is crucial for personalized orthotics, digital healthcare, and virtual fittings. However, existing methods struggle with incomplete scans and anatom…
Gaussian Head & Shoulders: High Fidelity Neural Upper Body Avatars with Anchor Gaussian Guided Texture Warping
Tianhao Wu, Jing Yang, Zhilin Guo +3
By equipping the most recent 3D Gaussian Splatting representation with head 3D morphable models (3DMM), existing methods manage to create head avatars with high fidelity. However,…
ARF-Plus: Controlling Perceptual Factors in Artistic Radiance Fields for 3D Scene Stylization
Wenzhao Li, Tianhao Wu, Fangcheng Zhong +1
The radiance fields style transfer is an emerging field that has recently gained popularity as a means of 3D scene stylization, thanks to the outstanding performance of neural radi…
Statistical shape representations for temporal registration of plant components in 3D
Karoline Heiwolt, Cengiz Öztireli, Grzegorz Cielniak
Plants are dynamic organisms and understanding temporal variations in vegetation is an essential problem for robots in the wild. However, associating repeated 3D scans of plants ac…