1 code implementation • ICCV 2023 • Noah Stier, Anurag Ranjan, Alex Colburn, Yajie Yan, Liang Yang, Fangchang Ma, Baptiste Angles
Recent works on 3D reconstruction from posed images have demonstrated that direct inference of scene-level 3D geometry without test-time optimization is feasible using deep neural networks, showing remarkable promise and high efficiency.
1 code implementation • ICCV 2023 • Noah Stier, Baptiste Angles, Liang Yang, Yajie Yan, Alex Colburn, Ming Chuang
Dense 3D reconstruction from RGB images traditionally assumes static camera pose estimates.
1 code implementation • CVPR 2021 • Baptiste Angles, Yuhe Jin, Simon Kornblith, Andrea Tagliasacchi, Kwang Moo Yi
We propose a deep network that can be trained to tackle image reconstruction and classification problems that involve detection of multiple object instances, without any supervision regarding their whereabouts.
no code implementations • 25 Sep 2019 • Baptiste Angles, Simon Kornblith, Shahram Izadi, Andrea Tagliasacchi, Kwang Moo Yi
We propose a deep network that can be trained to tackle image reconstruction and classification problems that involve detection of multiple object instances, without any supervision regarding their whereabouts.
1 code implementation • 17 Sep 2019 • Wei Jiang, Juan Camilo Gamboa Higuera, Baptiste Angles, Weiwei Sun, Mehrsan Javan, Kwang Moo Yi
We propose an optimization-based framework to register sports field templates onto broadcast videos.
1 code implementation • 26 Nov 2018 • Baptiste Angles, Yuhe Jin, Simon Kornblith, Andrea Tagliasacchi, Kwang Moo Yi
We propose a deep network that can be trained to tackle image reconstruction and classification problems that involve detection of multiple object instances, without any supervision regarding their whereabouts.
Anomaly Detection In Surveillance Videos Image Reconstruction