37 citations · 60 across the 9 of their papers we have counts for
9 papers
PoseDriver: A Unified Approach to Multi-Category Skeleton Detection for Autonomous Driving
Yasamin Borhani, Taylor Mordan, Yihan Wang +3
Object skeletons offer a concise representation of structural information, capturing essential aspects of posture and orientation that are crucial for autonomous driving applicatio…
Toward Reliable Human Pose Forecasting with Uncertainty
Saeed Saadatnejad, Mehrshad Mirmohammadi, Matin Daghyani +6
Recently, there has been an arms race of pose forecasting methods aimed at solving the spatio-temporal task of predicting a sequence of future 3D poses of a person given a sequence…
A generic diffusion-based approach for 3D human pose prediction in the wild
Saeed Saadatnejad, Ali Rasekh, Mohammadreza Mofayezi +4
Predicting 3D human poses in real-world scenarios, also known as human pose forecasting, is inevitably subject to noisy inputs arising from inaccurate 3D pose estimations and occlu…
Pedestrian Stop and Go Forecasting with Hybrid Feature Fusion
Dongxu Guo, Taylor Mordan, Alexandre Alahi
Forecasting pedestrians' future motions is essential for autonomous driving systems to safely navigate in urban areas. However, existing prediction algorithms often overly rely on…
A Shared Representation for Photorealistic Driving Simulators
Saeed Saadatnejad, Siyuan Li, Taylor Mordan +1
A powerful simulator highly decreases the need for real-world tests when training and evaluating autonomous vehicles. Data-driven simulators flourished with the recent advancement…
Do Pedestrians Pay Attention? Eye Contact Detection in the Wild
Younes Belkada, Lorenzo Bertoni, Romain Caristan +2
In urban or crowded environments, humans rely on eye contact for fast and efficient communication with nearby people. Autonomous agents also need to detect eye contact to interact…
Detecting 32 Pedestrian Attributes for Autonomous Vehicles
Taylor Mordan, Matthieu Cord, Patrick Pérez +1
Pedestrians are arguably one of the most safety-critical road users to consider for autonomous vehicles in urban areas. In this paper, we address the problem of jointly detecting p…
MonStereo: When Monocular and Stereo Meet at the Tail of 3D Human Localization
Lorenzo Bertoni, Sven Kreiss, Taylor Mordan +1
Monocular and stereo visions are cost-effective solutions for 3D human localization in the context of self-driving cars or social robots. However, they are usually developed indepe…
Deformable Part-based Fully Convolutional Network for Object Detection
Taylor Mordan, Nicolas Thome, Matthieu Cord +1
Existing region-based object detectors are limited to regions with fixed box geometry to represent objects, even if those are highly non-rectangular. In this paper we introduce DP-…