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20232026
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cs.CV2026

Matryoshka Gaussian Splatting

Zhilin Guo, Boqiao Zhang, Hakan Aktas +11

The ability to render scenes at adjustable fidelity from a single model, known as level of detail (LoD), is crucial for practical deployment of 3D Gaussian Splatting (3DGS). Existi…

cs.CV2026

PoseCraft: Tokenized 3D Body Landmark and Camera Conditioning for Photorealistic Human Image Synthesis

Zhilin Guo, Jing Yang, Kyle Fogarty +9

Digitizing humans and synthesizing photorealistic avatars with explicit 3D pose and camera controls are central to VR, telepresence, and entertainment. Existing skinning-based work…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

SYM3D: Learning Symmetric Triplanes for Better 3D-Awareness of GANs

Jing Yang, Kyle Fogarty, Fangcheng Zhong +1

Despite the growing success of 3D-aware GANs, which can be trained on 2D images to generate high-quality 3D assets, they still rely on multi-view images with camera annotations to…