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Found 11 papers, 11 papers with code
Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning
We propose to (i) rethink pairwise interactions with a self-attention mechanism, and (ii) jointly model Human-Robot as well as Human-Human interactions in the deep reinforcement learning framework.
PifPaf: Composite Fields for Human Pose Estimation
We propose a new bottom-up method for multi-person 2D human pose estimation that is particularly well suited for urban mobility such as self-driving cars and delivery robots.
Ranked #10 on
Keypoint Detection
on COCO test-dev
Deep Visual Re-Identification with Confidence
We argue that such loss function is not suited for the visual re-identification task hence propose to model confidence in the representation learning framework.
MonoLoco: Monocular 3D Pedestrian Localization and Uncertainty Estimation
We tackle the fundamentally ill-posed problem of 3D human localization from monocular RGB images.
Human Trajectory Forecasting in Crowds: A Deep Learning Perspective
In this work, we present an in-depth analysis of existing deep learning-based methods for modelling social interactions.
Ranked #3 on
Trajectory Prediction
on TrajNet++
MonStereo: When Monocular and Stereo Meet at the Tail of 3D Human Localization
Monocular and stereo visions are cost-effective solutions for 3D human localization in the context of self-driving cars or social robots.
Perceiving Humans: from Monocular 3D Localization to Social Distancing
Our neural network estimates human 3D body locations and their orientation with a measure of uncertainty.
Perceiving Traffic from Aerial Images
Drones or UAVs, equipped with different sensors, have been deployed in many places especially for urban traffic monitoring or last-mile delivery.
OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association
We present a generic neural network architecture that uses Composite Fields to detect and construct a spatio-temporal pose which is a single, connected graph whose nodes are the semantic keypoints (e. g., a person's body joints) in multiple frames.
Ranked #2 on
Car Pose Estimation
on ApolloCar3D
Deep Social Force
The Social Force model introduced by Helbing and Molnar in 1995 is a cornerstone of pedestrian simulation.
Keypoint Communities
We present a fast bottom-up method that jointly detects over 100 keypoints on humans or objects, also referred to as human/object pose estimation.
Ranked #1 on
Car Pose Estimation
on ApolloCar3D
