24 citations · 30 across the 5 of their papers we have counts for
5 papers
Improving and Evaluating Hand-Object Interaction Detection
Ahmad Darkhalil, Dima Damen, David Fouhey
Understanding hands and the objects they interact with, both directly and through tools, is a key step for tasks ranging from action perception to 3D reconstruction and robotics. O…
HD-EPIC: A Highly-Detailed Egocentric Video Dataset
Toby Perrett, Ahmad Darkhalil, Saptarshi Sinha +16
We present a validation dataset of newly-collected kitchen-based egocentric videos, manually annotated with highly detailed and interconnected ground-truth labels covering: recipe…
EgoPoints: Advancing Point Tracking for Egocentric Videos
Ahmad Darkhalil, Rhodri Guerrier, Adam W. Harley +1
We introduce EgoPoints, a benchmark for point tracking in egocentric videos. We annotate 4.7K challenging tracks in egocentric sequences. Compared to the popular TAP-Vid-DAVIS eval…
EPIC Fields: Marrying 3D Geometry and Video Understanding
Vadim Tschernezki, Ahmad Darkhalil, Zhifan Zhu +5
Neural rendering is fuelling a unification of learning, 3D geometry and video understanding that has been waiting for more than two decades. Progress, however, is still hampered by…
EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object Relations
Ahmad Darkhalil, Dandan Shan, Bin Zhu +6
We introduce VISOR, a new dataset of pixel annotations and a benchmark suite for segmenting hands and active objects in egocentric video. VISOR annotates videos from EPIC-KITCHENS,…