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20152025
most citedDepth-based hand pose estimation: methods, data, and challenges

18 citations · 18 across the 7 of their papers we have counts for

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cs.CV2025

HOSt3R: Keypoint-free Hand-Object 3D Reconstruction from RGB images

Anilkumar Swamy, Vincent Leroy, Philippe Weinzaepfel +2

Hand-object 3D reconstruction has become increasingly important for applications in human-robot interaction and immersive AR/VR experiences. A common approach for object-agnostic h…

cs.CV2025

HAMSt3R: Human-Aware Multi-view Stereo 3D Reconstruction

Sara Rojas, Matthieu Armando, Bernard Ghamen +3

Recovering the 3D geometry of a scene from a sparse set of uncalibrated images is a long-standing problem in computer vision. While recent learning-based approaches such as DUSt3R…

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

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.CV2022

PoseGPT: Quantization-based 3D Human Motion Generation and Forecasting

Thomas Lucas, Fabien Baradel, Philippe Weinzaepfel +1

We address the problem of action-conditioned generation of human motion sequences. Existing work falls into two categories: forecast models conditioned on observed past motions, or…

cs.CV2022

MonoNHR: Monocular Neural Human Renderer

Hongsuk Choi, Gyeongsik Moon, Matthieu Armando +3

Existing neural human rendering methods struggle with a single image input due to the lack of information in invisible areas and the depth ambiguity of pixels in visible areas. In…