output
20002026
most citedMethods for Interpreting and Understanding Deep Neural Networks

2.8k citations

Showing cs.GRShow all

27 papers · 1 filter

cs.GR2026

Volumetric Inverse Rendering via Neural Radiative Transfer

Ntumba Elie Nsampi, Adarsh Djeacoumar, Hans-Peter Seidel +2

Volumetric inverse rendering seeks to recover the optical properties of participating media from images. Existing approaches either rely on differentiable stochastic light transpor…

cs.GR2025

Step2Motion: Locomotion Reconstruction from Pressure Sensing Insoles

Jose Luis Ponton, Eduardo Alvarado, Lin Geng Foo +3

Human motion is fundamentally driven by continuous physical interaction with the environment. Whether walking, running, or simply standing, the forces exchanged between our feet an…

cs.GR2025★ 7 cited

IntrinsicEdit: Precise generative image manipulation in intrinsic space

Linjie Lyu, Valentin Deschaintre, Yannick Hold-Geoffroy +5

Generative diffusion models have advanced image editing with high-quality results and intuitive interfaces such as prompts and semantic drawing. However, these interfaces lack prec…

cs.GR2025

Interactive Stroke-based Neural SDF Sculpting

Fizza Rubab, Yiying Tong

Recent advances in implicit neural representations have made them a popular choice for modeling 3D geometry. However, directly editing these representations presents challenges due…

cs.GR2024★ 1 cited

Jump Restore Light Transport

Sascha Holl, Gurprit Singh, Hans-Peter Seidel

Markov chain Monte Carlo (MCMC) algorithms are indispensable when sampling from a complex, high-dimensional distribution by a conventional method is intractable. Even though MCMC i…

cs.GR2023★ 3 cited

Discovering Fatigued Movements for Virtual Character Animation

Noshaba Cheema, Rui Xu, Nam Hee Kim +5

Virtual character animation and movement synthesis have advanced rapidly during recent years, especially through a combination of extensive motion capture datasets and machine lear…