Search Results for author: Darren Cosker

Found 12 papers, 3 papers with code

DynaDog+T: A Parametric Animal Model for Synthetic Canine Image Generation

no code implementations15 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.

3D Pose Estimation Image Generation

RGBD-Dog: Predicting Canine Pose from RGBD Sensors

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.

Pose Estimation Pose Prediction

Unsupervised Attention-guided Image-to-Image Translation

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.

Translation Unsupervised Image-To-Image Translation

Unsupervised Attention-guided Image to Image Translation

2 code implementations6 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.

Translation Unsupervised Image-To-Image Translation

Learn to Model Motion from Blurry Footages

no code implementations19 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.

Optical Flow Estimation

Blur Robust Optical Flow using Motion Channel

no code implementations7 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.

Optical Flow Estimation

Drift Robust Non-rigid Optical Flow Enhancement for Long Sequences

no code implementations7 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.

Optical Flow Estimation

Optical Flow Estimation Using Laplacian Mesh Energy

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.

Optical Flow Estimation

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