Search Results for author: Christoph Mayer

Found 11 papers, 6 papers with code

Beyond SOT: Tracking Multiple Generic Objects at Once

1 code implementation22 Dec 2022 Christoph Mayer, Martin Danelljan, Ming-Hsuan Yang, Vittorio Ferrari, Luc van Gool, Alina Kuznetsova

Our approach achieves a 4x faster run-time in case of 10 concurrent objects compared to tracking each object independently and outperforms existing single object trackers on our new benchmark.

Attribute Object +1

AVisT: A Benchmark for Visual Object Tracking in Adverse Visibility

1 code implementation14 Aug 2022 Mubashir Noman, Wafa Al Ghallabi, Daniya Najiha, Christoph Mayer, Akshay Dudhane, Martin Danelljan, Hisham Cholakkal, Salman Khan, Luc van Gool, Fahad Shahbaz Khan

While being greatly benefiting to the tracking research, existing benchmarks do not pose the same difficulty as before with recent trackers achieving higher performance mainly due to (i) the introduction of more sophisticated transformers-based methods and (ii) the lack of diverse scenarios with adverse visibility such as, severe weather conditions, camouflage and imaging effects.

Visual Object Tracking Visual Tracking

Transforming Model Prediction for Tracking

1 code implementation CVPR 2022 Christoph Mayer, Martin Danelljan, Goutam Bhat, Matthieu Paul, Danda Pani Paudel, Fisher Yu, Luc van Gool

Optimization based tracking methods have been widely successful by integrating a target model prediction module, providing effective global reasoning by minimizing an objective function.

Ranked #21 on Visual Object Tracking on LaSOT (Precision metric)

Inductive Bias Visual Object Tracking

Robust Visual Tracking by Segmentation

2 code implementations21 Mar 2022 Matthieu Paul, Martin Danelljan, Christoph Mayer, Luc van Gool

We infer a bounding box from the segmentation mask, validate our tracker on challenging tracking datasets and achieve the new state of the art on LaSOT with a success AUC score of 69. 7%.

Decoder Segmentation +5

Best Practices in Pool-based Active Learning for Image Classification

no code implementations29 Sep 2021 Adrian Lang, Christoph Mayer, Radu Timofte

We emphasize aspects such as the importance of using data augmentation, the need of separating the contribution of a classification network and the acquisition strategy to the overall performance, the advantages that a proper initialization of the network can bring to AL.

Active Learning Benchmarking +3

Learning Target Candidate Association to Keep Track of What Not to Track

1 code implementation ICCV 2021 Christoph Mayer, Martin Danelljan, Danda Pani Paudel, Luc van Gool

To tackle the problem of lacking ground-truth correspondences between distractor objects in visual tracking, we propose a training strategy that combines partial annotations with self-supervision.

Visual Object Tracking Visual Tracking

Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression

2 code implementations CVPR 2020 Yawei Li, Shuhang Gu, Christoph Mayer, Luc van Gool, Radu Timofte

In this paper, we analyze two popular network compression techniques, i. e. filter pruning and low-rank decomposition, in a unified sense.

Efficient Video Semantic Segmentation with Labels Propagation and Refinement

no code implementations26 Dec 2019 Matthieu Paul, Christoph Mayer, Luc van Gool, Radu Timofte

(ii) On the GPU, two Convolutional Neural Networks: A main segmentation network that is used to predict dense semantic labels from scratch, and a Refiner that is designed to improve predictions from previous frames with the help of a fast Inconsistencies Attention Module (IAM).

Image Segmentation Optical Flow Estimation +5

Adversarial Sampling for Active Learning

no code implementations ICLR 2019 Christoph Mayer, Radu Timofte

This paper proposes asal, a new GAN based active learning method that generates high entropy samples.

Active Learning General Classification +1

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