8 citations · 12 across the 6 of their papers we have counts for
8 papers
Revisiting Modality Imbalance In Multimodal Pedestrian Detection
Arindam Das, Sudip Das, Ganesh Sistu +5
Multimodal learning, particularly for pedestrian detection, has recently received emphasis due to its capability to function equally well in several critical autonomous driving sce…
Deep Multi-Task Networks For Occluded Pedestrian Pose Estimation
Arindam Das, Sudip Das, Ganesh Sistu +5
Most of the existing works on pedestrian pose estimation do not consider estimating the pose of an occluded pedestrian, as the annotations of the occluded parts are not available i…
UnShadowNet: Illumination Critic Guided Contrastive Learning For Shadow Removal
Subhrajyoti Dasgupta, Arindam Das, Senthil Yogamani +4
Shadows are frequently encountered natural phenomena that significantly hinder the performance of computer vision perception systems in practical settings, e.g., autonomous driving…
Spatio-Contextual Deep Network Based Multimodal Pedestrian Detection For Autonomous Driving
Kinjal Dasgupta, Arindam Das, Sudip Das +2
Pedestrian Detection is the most critical module of an Autonomous Driving system. Although a camera is commonly used for this purpose, its quality degrades severely in low-light ni…
An End-to-End Framework for Unsupervised Pose Estimation of Occluded Pedestrians
Sudip Das, Perla Sai Raj Kishore, Ujjwal Bhattacharya
Pose estimation in the wild is a challenging problem, particularly in situations of (i) occlusions of varying degrees and (ii) crowded outdoor scenes. Most of the existing studies…
Scale-Invariant Multi-Oriented Text Detection in Wild Scene Images
Kinjal Dasgupta, Sudip Das, Ujjwal Bhattacharya
Automatic detection of scene texts in the wild is a challenging problem, particularly due to the difficulties in handling (i) occlusions of varying percentages, (ii) widely differe…