collaborators

7 papers

cs.CV2025

GASPACHO: Gaussian Splatting for Controllable Humans and Objects

Aymen Mir, Arthur Moreau, Helisa Dhamo +3

We present GASPACHO, a method for generating photorealistic, controllable renderings of human-object interactions from multi-view RGB video. Unlike prior work that reconstructs onl…

cs.GR2025

CoMapGS: Covisibility Map-based Gaussian Splatting for Sparse Novel View Synthesis

Youngkyoon Jang, Eduardo Pérez-Pellitero

We propose Covisibility Map-based Gaussian Splatting (CoMapGS), designed to recover underrepresented sparse regions in sparse novel view synthesis. CoMapGS addresses both high- and…

cs.CV2025

SCRREAM : SCan, Register, REnder And Map:A Framework for Annotating Accurate and Dense 3D Indoor Scenes with a Benchmark

HyunJun Jung, Weihang Li, Shun-Cheng Wu +8

Traditionally, 3d indoor datasets have generally prioritized scale over ground-truth accuracy in order to obtain improved generalization. However, using these datasets to evaluate…

cs.CV2024

FORCE: Physics-aware Human-object Interaction

Xiaohan Zhang, Bharat Lal Bhatnagar, Sebastian Starke +5

Interactions between human and objects are influenced not only by the object's pose and shape, but also by physical attributes such as object mass and surface friction. They introd…

cs.CV2024

AIM 2024 Sparse Neural Rendering Challenge: Methods and Results

Michal Nazarczuk, Sibi Catley-Chandar, Thomas Tanay +27

This paper reviews the challenge on Sparse Neural Rendering that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2024. This manuscript…

cs.CV2024

AIM 2024 Sparse Neural Rendering Challenge: Dataset and Benchmark

Michal Nazarczuk, Thomas Tanay, Sibi Catley-Chandar +3

Recent developments in differentiable and neural rendering have made impressive breakthroughs in a variety of 2D and 3D tasks, e.g. novel view synthesis, 3D reconstruction. Typical…