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Found 9 papers, 4 papers with code
TrackFlow: Multi-Object Tracking with Normalizing Flows
The field of multi-object tracking has recently seen a renewed interest in the good old schema of tracking-by-detection, as its simplicity and strong priors spare it from the complex design and painful babysitting of tracking-by-attention approaches.
MOTSynth: How Can Synthetic Data Help Pedestrian Detection and Tracking?
Deep learning-based methods for video pedestrian detection and tracking require large volumes of training data to achieve good performance.
Inter-Homines: Distance-Based Risk Estimation for Human Safety
In this document, we report our proposal for modeling the risk of possible contagiousity in a given area monitored by RGB cameras where people freely move and interact.
Compressed Volumetric Heatmaps for Multi-Person 3D Pose Estimation
At the core of the proposed method lies our Volumetric Heatmap Autoencoder, a fully-convolutional network tasked with the compression of ground-truth heatmaps into a dense intermediate representation.
Ranked #6 on
3D Human Pose Estimation
on Panoptic
(using extra training data)
Domain Translation with Conditional GANs: from Depth to RGB Face-to-Face
Can faces acquired by low-cost depth sensors be useful to catch some characteristic details of the face?
Can Adversarial Networks Hallucinate Occluded People With a Plausible Aspect?
When you see a person in a crowd, occluded by other persons, you miss visual information that can be used to recognize, re-identify or simply classify him or her.
Learning to Detect and Track Visible and Occluded Body Joints in a Virtual World
Multi-People Tracking in an open-world setting requires a special effort in precise detection.
Face-from-Depth for Head Pose Estimation on Depth Images
Therefore, we propose a complete framework for the estimation of the head and shoulder pose based on depth images only.
Generative Adversarial Models for People Attribute Recognition in Surveillance
In this paper we propose a deep architecture for detecting people attributes (e. g. gender, race, clothing ...) in surveillance contexts.
