1 code implementation • ICCV 2021 • Jeremy Reizenstein, Roman Shapovalov, Philipp Henzler, Luca Sbordone, Patrick Labatut, David Novotny
Traditional approaches for learning 3D object categories have been predominantly trained and evaluated on synthetic datasets due to the unavailability of real 3D-annotated category-centric data.
1 code implementation • CVPR 2020 • Philipp Henzler, Niloy J. Mitra, Tobias Ritschel
We propose a generative model of 2D and 3D natural textures with diversity, visual fidelity and at high computational efficiency.
no code implementations • 30 Jan 2018 • Stefan Hoermann, Philipp Henzler, Martin Bach, Klaus Dietmayer
We tackle the problem of object detection and pose estimation in a shared space downtown environment.
no code implementations • ICCV 2019 • Philipp Henzler, Niloy Mitra, Tobias Ritschel
We can successfully reconstruct 3D shapes from unstructured 2D images and extensively evaluate PlatonicGAN on a range of synthetic and real data sets achieving consistent improvements over baseline methods.
no code implementations • 20 Nov 2020 • Philipp Henzler, Christian Traum, Matthias Holtkemper, David Nabben, Marcel Erbe, Doris E. Reiter, Tilmann Kuhn, Suddhassatta Mahapatra, Karl Brunner, Denis V. Seletskiy, Alfred Leitenstorfer
Ultrafast transmission changes around the fundamental trion resonance are studied after exciting a p-shell exciton in a negatively charged II-VI quantum dot.
Mesoscale and Nanoscale Physics Quantum Physics
no code implementations • 23 Feb 2021 • Philipp Henzler, Valentin Deschaintre, Niloy J. Mitra, Tobias Ritschel
We learn a latent space for easy capture, consistent interpolation, and efficient reproduction of visual material appearance.
no code implementations • CVPR 2021 • Philipp Henzler, Jeremy Reizenstein, Patrick Labatut, Roman Shapovalov, Tobias Ritschel, Andrea Vedaldi, David Novotny
Our goal is to learn a deep network that, given a small number of images of an object of a given category, reconstructs it in 3D.
no code implementations • 21 Aug 2023 • Keunhong Park, Philipp Henzler, Ben Mildenhall, Jonathan T. Barron, Ricardo Martin-Brualla
We propose using a proxy problem to compute a whitening transform that eliminates the correlation between camera parameters and normalizes their effects, and we propose to use this transform as a preconditioner for the camera parameters during joint optimization.
no code implementations • 5 Dec 2023 • Rundi Wu, Ben Mildenhall, Philipp Henzler, Keunhong Park, Ruiqi Gao, Daniel Watson, Pratul P. Srinivasan, Dor Verbin, Jonathan T. Barron, Ben Poole, Aleksander Holynski
3D reconstruction methods such as Neural Radiance Fields (NeRFs) excel at rendering photorealistic novel views of complex scenes.