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Recovering 3d human mesh from monocular images: A survey
Estimating human pose and shape from monocular images is a long-standing problem in
computer vision. Since the release of statistical body models, 3D human mesh recovery has …
computer vision. Since the release of statistical body models, 3D human mesh recovery has …
Hugs: Human gaussian splats
Recent advances in neural rendering have improved both training and rendering times by
orders of magnitude. While these methods demonstrate state-of-the-art quality and speed …
orders of magnitude. While these methods demonstrate state-of-the-art quality and speed …
Champ: Controllable and consistent human image animation with 3d parametric guidance
In this study, we introduce a methodology for human image animation by leveraging a 3D
human parametric model within a latent diffusion framework to enhance shape alignment …
human parametric model within a latent diffusion framework to enhance shape alignment …
Reconstructing hands in 3d with transformers
We present an approach that can reconstruct hands in 3D from monocular input. Our
approach for Hand Mesh Recovery HaMeR follows a fully transformer-based architecture …
approach for Hand Mesh Recovery HaMeR follows a fully transformer-based architecture …
Gart: Gaussian articulated template models
Abstract We introduce Gaussian Articulated Template Model (GART) an explicit efficient and
expressive representation for non-rigid articulated subject capturing and rendering from …
expressive representation for non-rigid articulated subject capturing and rendering from …
Wham: Reconstructing world-grounded humans with accurate 3d motion
The estimation of 3D human motion from video has progressed rapidly but current methods
still have several key limitations. First most methods estimate the human in camera …
still have several key limitations. First most methods estimate the human in camera …
Tokenhmr: Advancing human mesh recovery with a tokenized pose representation
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 …
a focus on 3D accuracy. The current best methods leverage large datasets of 3D pseudo …
Deep learning for 3d human pose estimation and mesh recovery: A survey
Abstract 3D human pose estimation and mesh recovery have attracted widespread research
interest in many areas, such as computer vision, autonomous driving, and robotics. Deep …
interest in many areas, such as computer vision, autonomous driving, and robotics. Deep …
Chatpose: Chatting about 3d human pose
We introduce ChatPose a framework employing Large Language Models (LLMs) to
understand and reason about 3D human poses from images or textual descriptions. Our …
understand and reason about 3D human poses from images or textual descriptions. Our …
Paint-it: Text-to-texture synthesis via deep convolutional texture map optimization and physically-based rendering
We present Paint-it a text-driven high-fidelity texture map synthesis method for 3D meshes
via neural re-parameterized texture optimization. Paint-it synthesizes texture maps from a …
via neural re-parameterized texture optimization. Paint-it synthesizes texture maps from a …