1 citations · 2 across the 11 of their papers we have counts for
7 papers · 1 filter
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…
Enforcing View-Consistency in Class-Agnostic 3D Segmentation Fields
Corentin Dumery, Aoxiang Fan, Ren Li +2
Radiance Fields have become a powerful tool for modeling 3D scenes from multiple images. However, they remain difficult to segment into semantically meaningful regions. Some method…
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…
Reconstruction of Manipulated Garment with Guided Deformation Prior
Ren Li, Corentin Dumery, Zhantao Deng +1
Modeling the shape of garments has received much attention, but most existing approaches assume the garments to be worn by someone, which constrains the range of shapes they can as…
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…
Occlusion Resilient 3D Human Pose Estimation
Soumava Kumar Roy, Ilia Badanin, Sina Honari +1
Occlusions remain one of the key challenges in 3D body pose estimation from single-camera video sequences. Temporal consistency has been extensively used to mitigate their impact b…
Using Motion Cues to Supervise Single-Frame Body Pose and Shape Estimation in Low Data Regimes
Andrey Davydov, Alexey Sidnev, Artsiom Sanakoyeu +3
When enough annotated training data is available, supervised deep-learning algorithms excel at estimating human body pose and shape using a single camera. The effects of too little…