1 code implementation • 6 Aug 2024 • Joanna Kaleta, Kacper Kania, Tomasz Trzcinski, Marek Kowalski
Our approach yields high-quality scene reconstructions and enables realistic lighting synthesis under novel environment maps.
no code implementations • CVPR 2023 • Kacper Kania, Stephan J. Garbin, Andrea Tagliasacchi, Virginia Estellers, Kwang Moo Yi, Julien Valentin, Tomasz Trzciński, Marek Kowalski
Generating faithful visualizations of human faces requires capturing both coarse and fine-level details of the face geometry and appearance.
no code implementations • 1 Aug 2022 • Stephan J. Garbin, Marek Kowalski, Virginia Estellers, Stanislaw Szymanowicz, Shideh Rezaeifar, Jingjing Shen, Matthew Johnson, Julien Valentin
The recent increase in popularity of volumetric representations for scene reconstruction and novel view synthesis has put renewed focus on animating volumetric content at high visual quality and in real-time.
1 code implementation • CVPR 2022 • Kacper Kania, Kwang Moo Yi, Marek Kowalski, Tomasz Trzciński, Andrea Tagliasacchi
We extend neural 3D representations to allow for intuitive and interpretable user control beyond novel view rendering (i. e. camera control).
no code implementations • 1 Apr 2021 • Kacper Kania, Marek Kowalski, Tomasz Trzciński
The creation of plausible and controllable 3D human motion animations is a long-standing problem that requires a manual intervention of skilled artists.
1 code implementation • ICCV 2021 • Stephan J. Garbin, Marek Kowalski, Matthew Johnson, Jamie Shotton, Julien Valentin
Recent work on Neural Radiance Fields (NeRF) showed how neural networks can be used to encode complex 3D environments that can be rendered photorealistically from novel viewpoints.
no code implementations • 16 Jul 2020 • Tadas Baltrusaitis, Erroll Wood, Virginia Estellers, Charlie Hewitt, Sebastian Dziadzio, Marek Kowalski, Matthew Johnson, Thomas J. Cashman, Jamie Shotton
Analysis of faces is one of the core applications of computer vision, with tasks ranging from landmark alignment, head pose estimation, expression recognition, and face recognition among others.
no code implementations • ECCV 2020 • Stephan J. Garbin, Marek Kowalski, Matthew Johnson, Jamie Shotton
In contrast to computer graphics approaches, generative models learned from more readily available 2D image data have been shown to produce samples of human faces that are hard to distinguish from real data.
2 code implementations • ECCV 2020 • Marek Kowalski, Stephan J. Garbin, Virginia Estellers, Tadas Baltrušaitis, Matthew Johnson, Jamie Shotton
Our ability to sample realistic natural images, particularly faces, has advanced by leaps and bounds in recent years, yet our ability to exert fine-tuned control over the generative process has lagged behind.
1 code implementation • 1 Feb 2018 • Marek Kowalski, Zbigniew Nasarzewski, Grzegorz Galinski, Piotr Garbat
Head pose estimation is accomplished by fitting a deformable 3D model to the landmarks localized using face alignment.
no code implementations • 6 Jun 2017 • Marek Kowalski, Jacek Naruniec
In this work we present a face alignment pipeline based on two novel methods: weighted splitting for K-cluster Regression Forests and 3D Affine Pose Regression for face shape initialization.
3 code implementations • 6 Jun 2017 • Marek Kowalski, Jacek Naruniec, Tomasz Trzcinski
Our method uses entire face images at all stages, contrary to the recently proposed face alignment methods that rely on local patches.
Ranked #4 on Face Alignment on 300W Split 2 (NME (inter-ocular) metric)