Ahmad Darkhalil
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View article: HD-EPIC: A Highly-Detailed Egocentric Video Dataset
HD-EPIC: A Highly-Detailed Egocentric Video Dataset Open
We present a validation dataset of newly-collected kitchen-based egocentric videos, manually annotated with highly detailed and interconnected ground-truth labels covering: recipe steps, fine-grained actions, ingredients with nutritional v…
View article: EgoPoints: Advancing Point Tracking for Egocentric Videos
EgoPoints: Advancing Point Tracking for Egocentric Videos Open
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 evaluation benchmark, we include 9x more points that go out-of-…
View article: EPIC Fields: Marrying 3D Geometry and Video Understanding
EPIC Fields: Marrying 3D Geometry and Video Understanding Open
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 a lack of suitable datasets and benchmarks. To address thi…
View article: EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object Relations
EPIC-KITCHENS VISOR Benchmark: VIdeo Segmentations and Object Relations Open
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, which comes with a new set of challenges not encountered i…