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20162024
most citedFLARE: Fast Learning of Animatable and Relightable Mesh Avatars

31 citations · 114 across the 21 of their papers we have counts for

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18 papers · 1 filter

cs.CV2024

TokenHMR: Advancing Human Mesh Recovery with a Tokenized Pose Representation

Sai Kumar Dwivedi, Yu Sun, Priyanka Patel +2

We address the problem of regressing 3D human pose and shape from a single image, with a focus on 3D accuracy. The current best methods leverage large datasets of 3D pseudo-ground-…

cs.CV20241 cited

WANDR: Intention-guided Human Motion Generation

Markos Diomataris, Nikos Athanasiou, Omid Taheri +3

Synthesizing natural human motions that enable a 3D human avatar to walk and reach for arbitrary goals in 3D space remains an unsolved problem with many applications. Existing meth…

cs.CV2024

Generating Human Interaction Motions in Scenes with Text Control

Hongwei Yi, Justus Thies, Michael J. Black +2

We present TeSMo, a method for text-controlled scene-aware motion generation based on denoising diffusion models. Previous text-to-motion methods focus on characters in isolation w…

cs.CV2024

Explorative Inbetweening of Time and Space

Haiwen Feng, Zheng Ding, Zhihao Xia +4

We introduce bounded generation as a generalized task to control video generation to synthesize arbitrary camera and subject motion based only on a given start and end frame. Our o…

cs.CV2023

HMP: Hand Motion Priors for Pose and Shape Estimation from Video

Enes Duran, Muhammed Kocabas, Vasileios Choutas +2

Understanding how humans interact with the world necessitates accurate 3D hand pose estimation, a task complicated by the hand's high degree of articulation, frequent occlusions, s…

cs.CV202331 cited

FLARE: Fast Learning of Animatable and Relightable Mesh Avatars

Shrisha Bharadwaj, Yufeng Zheng, Otmar Hilliges +2

Our goal is to efficiently learn personalized animatable 3D head avatars from videos that are geometrically accurate, realistic, relightable, and compatible with current rendering…