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20152026
most citedR2D2: Repeatable and Reliable Detector and Descriptor

356 citations · 1.3k across the 40 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CV2024

CondiMen: Conditional Multi-Person Mesh Recovery

Brégier Romain, Baradel Fabien, Lucas Thomas +4

Multi-person human mesh recovery (HMR) consists in detecting all individuals in a given input image, and predicting the body shape, pose, and 3D location for each detected person.…

cs.CV2024

MASt3R-SfM: a Fully-Integrated Solution for Unconstrained Structure-from-Motion

Bardienus Duisterhof, Lojze Zust, Philippe Weinzaepfel +3

Structure-from-Motion (SfM), a task aiming at jointly recovering camera poses and 3D geometry of a scene given a set of images, remains a hard problem with still many open challeng…

cs.CV2024

PoseEmbroider: Towards a 3D, Visual, Semantic-aware Human Pose Representation

Ginger Delmas, Philippe Weinzaepfel, Francesc Moreno-Noguer +1

Aligning multiple modalities in a latent space, such as images and texts, has shown to produce powerful semantic visual representations, fueling tasks like image captioning, text-t…

cs.CV2024

UNIC: Universal Classification Models via Multi-teacher Distillation

Mert Bulent Sariyildiz, Philippe Weinzaepfel, Thomas Lucas +2

Pretrained models have become a commodity and offer strong results on a broad range of tasks. In this work, we focus on classification and seek to learn a unique encoder able to ta…

cs.CV2024

Purposer: Putting Human Motion Generation in Context

Nicolas Ugrinovic, Thomas Lucas, Fabien Baradel +3

We present a novel method to generate human motion to populate 3D indoor scenes. It can be controlled with various combinations of conditioning signals such as a path in a scene, t…

cs.CV2024

Weatherproofing Retrieval for Localization with Generative AI and Geometric Consistency

Yannis Kalantidis, Mert Bülent Sarıyıldız, Rafael S. Rezende +3

State-of-the-art visual localization approaches generally rely on a first image retrieval step whose role is crucial. Yet, retrieval often struggles when facing varying conditions,…

cs.CV2024★ 1 cited

Multi-HMR: Multi-Person Whole-Body Human Mesh Recovery in a Single Shot

Fabien Baradel, Matthieu Armando, Salma Galaaoui +4

We present Multi-HMR, a strong sigle-shot model for multi-person 3D human mesh recovery from a single RGB image. Predictions encompass the whole body, i.e., including hands and fac…