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cs.CV2026

DeepShapeMatchingKit: Accelerated Functional Map Solver and Shape Matching Pipelines Revisited

Yizheng Xie, Lennart Bastian, Congyue Deng +3

Deep functional maps, leveraging learned feature extractors and spectral correspondence solvers, are fundamental to non-rigid 3D shape matching. Based on an analysis of open-source…

cs.CV2026

True Self-Supervised Novel View Synthesis is Transferable

Thomas W. Mitchel, Hyunwoo Ryu, Vincent Sitzmann

In this paper, we identify that the key criterion for determining whether a model is truly capable of novel view synthesis (NVS) is transferability: Whether any pose representation…

cs.CV2026

Scaling View Synthesis Transformers

Evan Kim, Hyunwoo Ryu, Thomas W. Mitchel +1

Geometry-free view synthesis transformers have recently achieved state-of-the-art performance in Novel View Synthesis (NVS), outperforming traditional approaches that rely on expli…

cs.CV2024

Neural Isometries: Taming Transformations for Equivariant ML

Thomas W. Mitchel, Michael Taylor, Vincent Sitzmann

Real-world geometry and 3D vision tasks are replete with challenging symmetries that defy tractable analytical expression. In this paper, we introduce Neural Isometries, an autoenc…

cs.CV2024

Single Mesh Diffusion Models with Field Latents for Texture Generation

Thomas W. Mitchel, Carlos Esteves, Ameesh Makadia

We introduce a framework for intrinsic latent diffusion models operating directly on the surfaces of 3D shapes, with the goal of synthesizing high-quality textures. Our approach is…