1 citations · 2 across the 8 of their papers we have counts for
8 papers · 1 filter
4DCodeBench: Benchmarking Agents on Inverse Graphics of Dynamic Scenes
Ruihong Shen, Žiga Kovačič, Peter Kulits +6
We introduce 4DCodeBench, a benchmark for 4D inverse graphics through code generation, in which agents reconstruct dynamic scenes from video as executable graphics programs. To acc…
BrickNet: Graph-Backed Generative Brick Assembly
Peter Kulits, Cordelia Schmid
We train a language model to generate LEGO-brick build sequences. While prior work has been restricted to discrete, voxel-like towers, we consider a much broader set of pieces, enc…
Generative Zoo
Tomasz Niewiadomski, Anastasios Yiannakidis, Hanz Cuevas-Velasquez +4
The model-based estimation of 3D animal pose and shape from images enables computational modeling of animal behavior. Training models for this purpose requires large amounts of lab…
Reconstructing Animals and the Wild
Peter Kulits, Michael J. Black, Silvia Zuffi
The idea of 3D reconstruction as scene understanding is foundational in computer vision. Reconstructing 3D scenes from 2D visual observations requires strong priors to disambiguate…
Re-Thinking Inverse Graphics With Large Language Models
Peter Kulits, Haiwen Feng, Weiyang Liu +2
Inverse graphics -- the task of inverting an image into physical variables that, when rendered, enable reproduction of the observed scene -- is a fundamental challenge in computer…
Text-Guided Generation and Editing of Compositional 3D Avatars
Hao Zhang, Yao Feng, Peter Kulits +3
Our goal is to create a realistic 3D facial avatar with hair and accessories using only a text description. While this challenge has attracted significant recent interest, existing…
Reconstructing Signing Avatars From Video Using Linguistic Priors
Maria-Paola Forte, Peter Kulits, Chun-Hao Huang +4
Sign language (SL) is the primary method of communication for the 70 million Deaf people around the world. Video dictionaries of isolated signs are a core SL learning tool. Replaci…
Generalizing Neural Human Fitting to Unseen Poses With Articulated SE(3) Equivariance
Haiwen Feng, Peter Kulits, Shichen Liu +2
We address the problem of fitting a parametric human body model (SMPL) to point cloud data. Optimization-based methods require careful initialization and are prone to becoming trap…