6 papers
SMF: Template-free and Rig-free Animation Transfer using Kinetic Codes
Sanjeev Muralikrishnan, Niladri Shekhar Dutt, Niloy J. Mitra
Animation retargetting applies sparse motion description (e.g., keypoint sequences) to a character mesh to produce a semantically plausible and temporally coherent full-body mesh s…
Temporal Residual Jacobians For Rig-free Motion Transfer
Sanjeev Muralikrishnan, Niladri Shekhar Dutt, Siddhartha Chaudhuri +4
We introduce Temporal Residual Jacobians as a novel representation to enable data-driven motion transfer. Our approach does not assume access to any rigging or intermediate shape k…
Diffusion 3D Features (Diff3F): Decorating Untextured Shapes with Distilled Semantic Features
Niladri Shekhar Dutt, Sanjeev Muralikrishnan, Niloy J. Mitra
We present Diff3F as a simple, robust, and class-agnostic feature descriptor that can be computed for untextured input shapes (meshes or point clouds). Our method distills diffusio…
BLiSS: Bootstrapped Linear Shape Space
Sanjeev Muralikrishnan, Chun-Hao Paul Huang, Duygu Ceylan +1
Morphable models are fundamental to numerous human-centered processes as they offer a simple yet expressive shape space. Creating such morphable models, however, is both tedious an…
GLASS: Geometric Latent Augmentation for Shape Spaces
Sanjeev Muralikrishnan, Siddhartha Chaudhuri, Noam Aigerman +3
We investigate the problem of training generative models on a very sparse collection of 3D models. We use geometrically motivated energies to augment and thus boost a sparse collec…
Tags2Parts: Discovering Semantic Regions from Shape Tags
Sanjeev Muralikrishnan, Vladimir G. Kim, Siddhartha Chaudhuri
We propose a novel method for discovering shape regions that strongly correlate with user-prescribed tags. For example, given a collection of chairs tagged as either "has armrest"…