3 citations · 5 across the 8 of their papers we have counts for
8 papers
One Graph to Track Them All: Dynamic GNNs for Single- and Multi-View Tracking
Martin Engilberge, Ivan Vrkic, Friedrich Wilke Grosche +3
This work presents a unified, fully differentiable model for multi-people tracking that learns to associate detections into trajectories without relying on pre-computed tracklets.…
No Identity, no problem: Motion through detection for people tracking
Martin Engilberge, F. Wilke Grosche, Pascal Fua
Tracking-by-detection has become the de facto standard approach to people tracking. To increase robustness, some approaches incorporate re-identification using appearance models an…
Addressing the Elephant in the Room: Robust Animal Re-Identification with Unsupervised Part-Based Feature Alignment
Yingxue Yu, Vidit Vidit, Andrey Davydov +2
Animal Re-ID is crucial for wildlife conservation, yet it faces unique challenges compared to person Re-ID. First, the scarcity and lack of diversity in datasets lead to background…
CLOAF: CoLlisiOn-Aware Human Flow
Andrey Davydov, Martin Engilberge, Mathieu Salzmann +1
Even the best current algorithms for estimating body 3D shape and pose yield results that include body self-intersections. In this paper, we present CLOAF, which exploits the diffe…
Learning Transformations To Reduce the Geometric Shift in Object Detection
Vidit Vidit, Martin Engilberge, Mathieu Salzmann
The performance of modern object detectors drops when the test distribution differs from the training one. Most of the methods that address this focus on object appearance changes…
CLIP the Gap: A Single Domain Generalization Approach for Object Detection
Vidit Vidit, Martin Engilberge, Mathieu Salzmann
Single Domain Generalization (SDG) tackles the problem of training a model on a single source domain so that it generalizes to any unseen target domain. While this has been well st…
Multi-view Tracking Using Weakly Supervised Human Motion Prediction
Martin Engilberge, Weizhe Liu, Pascal Fua
Multi-view approaches to people-tracking have the potential to better handle occlusions than single-view ones in crowded scenes. They often rely on the tracking-by-detection paradi…
Two-level Data Augmentation for Calibrated Multi-view Detection
Martin Engilberge, Haixin Shi, Zhiye Wang +1
Data augmentation has proven its usefulness to improve model generalization and performance. While it is commonly applied in computer vision application when it comes to multi-view…