47 citations · 114 across the 9 of their papers we have counts for
14 papers · 1 filter
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,…
Causal Scene BERT: Improving object detection by searching for challenging groups of data
Cinjon Resnick, Or Litany, Amlan Kar +4
Modern computer vision applications rely on learning-based perception modules parameterized with neural networks for tasks like object detection. These modules frequently have low…
ATISS: Autoregressive Transformers for Indoor Scene Synthesis
Despoina Paschalidou, Amlan Kar, Maria Shugrina +3
The ability to synthesize realistic and diverse indoor furniture layouts automatically or based on partial input, unlocks many applications, from better interactive 3D tools to dat…
Towards Good Practices for Efficiently Annotating Large-Scale Image Classification Datasets
Yuan-Hong Liao, Amlan Kar, Sanja Fidler
Data is the engine of modern computer vision, which necessitates collecting large-scale datasets. This is expensive, and guaranteeing the quality of the labels is a major challenge…
Fed-Sim: Federated Simulation for Medical Imaging
Daiqing Li, Amlan Kar, Nishant Ravikumar +2
Labelling data is expensive and time consuming especially for domains such as medical imaging that contain volumetric imaging data and require expert knowledge. Exploiting a larger…
Meta-Sim2: Unsupervised Learning of Scene Structure for Synthetic Data Generation
Jeevan Devaranjan, Amlan Kar, Sanja Fidler
Procedural models are being widely used to synthesize scenes for graphics, gaming, and to create (labeled) synthetic datasets for ML. In order to produce realistic and diverse scen…