44 citations · 177 across the 20 of their papers we have counts for
5 papers · 1 filter
SkyScenes: A Synthetic Dataset for Aerial Scene Understanding
Sahil Khose, Anisha Pal, Aayushi Agarwal +3
Real-world aerial scene understanding is limited by a lack of datasets that contain densely annotated images curated under a diverse set of conditions. Due to inherent challenges i…
AUGCAL: Improving Sim2Real Adaptation by Uncertainty Calibration on Augmented Synthetic Images
Prithvijit Chattopadhyay, Bharat Goyal, Boglarka Ecsedi +2
Synthetic data (SIM) drawn from simulators have emerged as a popular alternative for training models where acquiring annotated real-world images is difficult. However, transferring…
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks
Micah Goldblum, Hossein Souri, Renkun Ni +10
Neural network based computer vision systems are typically built on a backbone, a pretrained or randomly initialized feature extractor. Several years ago, the default option was an…
LANCE: Stress-testing Visual Models by Generating Language-guided Counterfactual Images
Viraj Prabhu, Sriram Yenamandra, Prithvijit Chattopadhyay +1
We propose an automated algorithm to stress-test a trained visual model by generating language-guided counterfactual test images (LANCE). Our method leverages recent progress in la…
Benchmarking Low-Shot Robustness to Natural Distribution Shifts
Aaditya Singh, Kartik Sarangmath, Prithvijit Chattopadhyay +1
Robustness to natural distribution shifts has seen remarkable progress thanks to recent pre-training strategies combined with better fine-tuning methods. However, such fine-tuning…