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20142024
most citedOn Rendering Synthetic Images for Training an Object Detector

120 citations · 144 across the 16 of their papers we have counts for

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15 papers · 1 filter

cs.CV2024

MedTet: An Online Motion Model for 4D Heart Reconstruction

Yihong Chen, Jiancheng Yang, Deniz Sayin Mercadier +2

We present a novel approach to reconstruction of 3D cardiac motion from sparse intraoperative data. While existing methods can accurately reconstruct 3D organ geometries from full…

cs.CV2024

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…

cs.CV2024

Vision-Based Power Line Cables and Pylons Detection for Low Flying Aircraft

Jakub Gwizdała, Doruk Oner, Soumava Kumar Roy +6

Power lines are dangerous for low-flying aircraft, especially in low-visibility conditions. Thus, a vision-based system able to analyze the aircraft's surroundings and to provide t…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024

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…