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Found 15 papers, 9 papers with code
FreeCloth: Free-form Generation Enhances Challenging Clothed Human Modeling
For deformed regions close to the body, we leverage LBS to handle the deformation.
SAT-HMR: Real-Time Multi-Person 3D Mesh Estimation via Scale-Adaptive Tokens
While current one-stage methods, which follow a DETR-style pipeline, achieve state-of-the-art (SOTA) performance with high-resolution inputs, we observe that this particularly benefits the estimation of individuals in smaller scales of the image (e. g., those far from the camera), but at the cost of significantly increased computation overhead.
AlphaChimp: Tracking and Behavior Recognition of Chimpanzees
Understanding non-human primate behavior is crucial for improving animal welfare, modeling social behavior, and gaining insights into both distinctly human and shared behaviors.
Scaling Up Dynamic Human-Scene Interaction Modeling
Confronting the challenges of data scarcity and advanced motion synthesis in human-scene interaction modeling, we introduce the TRUMANS dataset alongside a novel HSI motion synthesis method.
Efficient Action Counting with Dynamic Queries
Temporal repetition counting aims to quantify the repeated action cycles within a video.
Real-time Holistic Robot Pose Estimation with Unknown States
Estimating robot pose from RGB images is a crucial problem in computer vision and robotics.
Ranked #1 on
Robot Pose Estimation
on DREAM-dataset
ScoreHypo: Probabilistic Human Mesh Estimation with Hypothesis Scoring
Experimental results demonstrate that HypoNet outperforms existing state-of-the-art probabilistic methods as a multi-hypothesis mesh estimator.
ChimpACT: A Longitudinal Dataset for Understanding Chimpanzee Behaviors
ChimpACT is both comprehensive and challenging, consisting of 163 videos with a cumulative 160, 500 frames, each richly annotated with detection, identification, pose estimation, and fine-grained spatiotemporal behavior labels.
Human Motion Generation: A Survey
In this survey, we present a comprehensive literature review of human motion generation, which, to the best of our knowledge, is the first of its kind in this field.
3D Human Mesh Estimation from Virtual Markers
The advanced motion capture systems solve the problem by placing dense physical markers on the body surface, which allows to extract realistic meshes from their non-rigid motions.
Ranked #1 on
3D Human Pose Estimation
on Surreal
GFPose: Learning 3D Human Pose Prior with Gradient Fields
During the denoising process, GFPose implicitly incorporates pose priors in gradients and unifies various discriminative and generative tasks in an elegant framework.
MotionBERT: A Unified Perspective on Learning Human Motion Representations
We present a unified perspective on tackling various human-centric video tasks by learning human motion representations from large-scale and heterogeneous data resources.
Ranked #1 on
Monocular 3D Human Pose Estimation
on Human3.6M
(using extra training data)
VirtualPose: Learning Generalizable 3D Human Pose Models from Virtual Data
While monocular 3D pose estimation seems to have achieved very accurate results on the public datasets, their generalization ability is largely overlooked.
3D Multi-Person Pose Estimation (absolute)
3D Pose Estimation
Context Modeling in 3D Human Pose Estimation: A Unified Perspective
By comparing the two methods, we found that the end-to-end training scheme in GNN and the limb length constraints in PSM are two complementary factors to improve results.
Ranked #65 on
3D Human Pose Estimation
on MPI-INF-3DHP
(AUC metric)
HAPPIER: Hierarchical Polyphonic Music Generative RNN
Generating polyphonic music with coherent global structure is a major challenge for automatic composition algorithms.
