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Found 10 papers, 5 papers with code
3D Human Pose Estimation with Occlusions: Introducing BlendMimic3D Dataset and GCN Refinement
In the field of 3D Human Pose Estimation (HPE), accurately estimating human pose, especially in scenarios with occlusions, is a significant challenge.
Latent Embedding Clustering for Occlusion Robust Head Pose Estimation
Head pose estimation has become a crucial area of research in computer vision given its usefulness in a wide range of applications, including robotics, surveillance, or driver attention monitoring.
2D Image head pose estimation via latent space regression under occlusion settings
Head orientation is a challenging Computer Vision problem that has been extensively researched having a wide variety of applications.
Ranked #4 on
Head Pose Estimation
on BIWI
Hyperbolic vs Euclidean Embeddings in Few-Shot Learning: Two Sides of the Same Coin
Recent research in representation learning has shown that hierarchical data lends itself to low-dimensional and highly informative representations in hyperbolic space.
Scoring Cycling Environments Perceived Safety using Pairwise Image Comparisons
Furthermore, this approach facilitates the continuous assessment of changing cycling environments, allows for a short-term evaluation of measures, and is efficiently deployed in different locations or contexts.
A Cluster-Based Trip Prediction Graph Neural Network Model for Bike Sharing Systems
Good knowledge of users' transition patterns is a decisive contribution to the quality and operability of the service.
Rotation Averaging in a Split Second: A Primal-Dual Method and a Closed-Form for Cycle Graphs
A cornerstone of geometric reconstruction, rotation averaging seeks the set of absolute rotations that optimally explains a set of measured relative orientations between them.
Subspace Segmentation by Successive Approximations: A Method for Low-Rank and High-Rank Data with Missing Entries
We propose a method to reconstruct and cluster incomplete high-dimensional data lying in a union of low-dimensional subspaces.
Understanding People Flow in Transportation Hubs
Results show that our methodology is able to successfully summarize the representative patterns for such a long observation period, providing relevant information for airport management.
A Context Aware and Video-Based Risk Descriptor for Cyclists
From smartphone sequences of images, this generic framework is able to automatically identify events considering different risk criteria based on the cyclist's motion and object detection.
