18 citations · 46 across the 7 of their papers we have counts for
10 papers
Beyond SOT: Tracking Multiple Generic Objects at Once
Christoph Mayer, Martin Danelljan, Ming-Hsuan Yang +3
Generic Object Tracking (GOT) is the problem of tracking target objects, specified by bounding boxes in the first frame of a video. While the task has received much attention in th…
AVisT: A Benchmark for Visual Object Tracking in Adverse Visibility
Mubashir Noman, Wafa Al Ghallabi, Daniya Najiha +7
One of the key factors behind the recent success in visual tracking is the availability of dedicated benchmarks. While being greatly benefiting to the tracking research, existing b…
Transforming Model Prediction for Tracking
Christoph Mayer, Martin Danelljan, Goutam Bhat +4
Optimization based tracking methods have been widely successful by integrating a target model prediction module, providing effective global reasoning by minimizing an objective fun…
Robust Visual Tracking by Segmentation
Matthieu Paul, Martin Danelljan, Christoph Mayer +1
Estimating the target extent poses a fundamental challenge in visual object tracking. Typically, trackers are box-centric and fully rely on a bounding box to define the target in t…
Learning Target Candidate Association to Keep Track of What Not to Track
Christoph Mayer, Martin Danelljan, Danda Pani Paudel +1
The presence of objects that are confusingly similar to the tracked target, poses a fundamental challenge in appearance-based visual tracking. Such distractor objects are easily mi…
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression
Yawei Li, Shuhang Gu, Christoph Mayer +2
In this paper, we analyze two popular network compression techniques, i.e. filter pruning and low-rank decomposition, in a unified sense. By simply changing the way the sparsity re…
Efficient Video Semantic Segmentation with Labels Propagation and Refinement
Matthieu Paul, Christoph Mayer, Luc Van Gool +1
This paper tackles the problem of real-time semantic segmentation of high definition videos using a hybrid GPU / CPU approach. We propose an Efficient Video Segmentation(EVS) pipel…
Adversarial Feature Distribution Alignment for Semi-Supervised Learning
Christoph Mayer, Matthieu Paul, Radu Timofte
Training deep neural networks with only a few labeled samples can lead to overfitting. This is problematic in semi-supervised learning where only a few labeled samples are availabl…
Adversarial Sampling for Active Learning
Christoph Mayer, Radu Timofte
This paper proposes asal, a new GAN based active learning method that generates high entropy samples. Instead of directly annotating the synthetic samples, ASAL searches similar sa…
Layer formation and relaminarisation in plane Couette flow with spanwise stratification
Dan Lucas, C. P. Caulfield, Rich R. Kerswell
Recent research has shed light on the role of coherent structures in forming layers when stably stratified turbulence is forced with horizontal shear (Lucas, Caulfield & Kerswell,…