2 code implementations • 6 Jun 2018 • Youssef A. Mejjati, Christian Richardt, James Tompkin, Darren Cosker, Kwang In Kim
Current unsupervised image-to-image translation techniques struggle to focus their attention on individual objects without altering the background or the way multiple objects interact within a scene.
1 code implementation • NeurIPS 2018 • Youssef Alami Mejjati, Christian Richardt, James Tompkin, Darren Cosker, Kwang In Kim
Current unsupervised image-to-image translation techniques struggle to focus their attention on individual objects without altering the background or the way multiple objects interact within a scene.
1 code implementation • CVPR 2020 • Sinead Kearney, Wenbin Li, Martin Parsons, Kwang In Kim, Darren Cosker
We evaluate our model on both synthetic and real RGBD images and compare our results to previously published work fitting canine models to images.
1 code implementation • ICCV 2023 • Siwei Zhang, Qianli Ma, Yan Zhang, Sadegh Aliakbarian, Darren Cosker, Siyu Tang
One of the biggest challenges of this task is severe body truncation due to close social distances in egocentric scenarios, which brings large pose ambiguities for unseen body parts.
no code implementations • 19 Apr 2017 • Wenbin Li, Da Chen, Zhihan Lv, Yan Yan, Darren Cosker
It is difficult to recover the motion field from a real-world footage given a mixture of camera shake and other photometric effects.
no code implementations • 26 Mar 2016 • Wenbin Li, Darren Cosker, Zhihan Lv, Matthew Brown
In this paper we present a dense ground truth dataset of nonrigidly deforming real-world scenes.
no code implementations • 26 Mar 2016 • Wenbin Li, Darren Cosker
Non-rigid video interpolation is a common computer vision task.
no code implementations • 7 Mar 2016 • Wenbin Li, Yang Chen, JeeHang Lee, Gang Ren, Darren Cosker
It is hard to estimate optical flow given a realworld video sequence with camera shake and other motion blur.
no code implementations • 7 Mar 2016 • Wenbin Li, Darren Cosker, Matthew Brown
We demonstrate the success of our approach by showing significant error reduction on 6 popular optical flow algorithms applied to a range of real-world nonrigid benchmarks.
no code implementations • CVPR 2018 • Youssef A. Mejjati, Darren Cosker, Kwang In Kim
We tackle this by considering task-specific estimators as random variables.
no code implementations • CVPR 2013 • Wenbin Li, Darren Cosker, Matthew Brown, Rui Tang
In this paper we present a novel non-rigid optical flow algorithm for dense image correspondence and non-rigid registration.
no code implementations • 15 Jul 2021 • Jake Deane, Sinead Kearney, Kwang In Kim, Darren Cosker
Synthetic data is becoming increasingly common for training computer vision models for a variety of tasks.
no code implementations • ICCV 2021 • Andrea Dittadi, Sebastian Dziadzio, Darren Cosker, Ben Lundell, Thomas J. Cashman, Jamie Shotton
The increased availability and maturity of head-mounted and wearable devices opens up opportunities for remote communication and collaboration.
no code implementations • ICCV 2023 • Balamurugan Thambiraja, Ikhsanul Habibie, Sadegh Aliakbarian, Darren Cosker, Christian Theobalt, Justus Thies
To address this, we present Imitator, a speech-driven facial expression synthesis method, which learns identity-specific details from a short input video and produces novel facial expressions matching the identity-specific speaking style and facial idiosyncrasies of the target actor.
no code implementations • ICCV 2023 • Sadegh Aliakbarian, Fatemeh Saleh, David Collier, Pashmina Cameron, Darren Cosker
Generating both plausible and accurate full body avatar motion is the key to the quality of immersive experiences in mixed reality scenarios.
no code implementations • 1 Dec 2023 • Balamurugan Thambiraja, Sadegh Aliakbarian, Darren Cosker, Justus Thies
To enable stochasticity as well as motion editing, we propose a lightweight audio-conditioned diffusion model for 3D facial motion.