16 citations · 38 across the 9 of their papers we have counts for
11 papers · 1 filter
Can Reasons Help Improve Pedestrian Intent Estimation? A Cross-Modal Approach
Vaishnavi Khindkar, Vineeth Balasubramanian, Chetan Arora +2
With the increased importance of autonomous navigation systems has come an increasing need to protect the safety of Vulnerable Road Users (VRUs) such as pedestrians. Predicting ped…
IDD-3D: Indian Driving Dataset for 3D Unstructured Road Scenes
Shubham Dokania, A. H. Abdul Hafez, Anbumani Subramanian +2
Autonomous driving and assistance systems rely on annotated data from traffic and road scenarios to model and learn the various object relations in complex real-world scenarios. Pr…
Detecting, Tracking and Counting Motorcycle Rider Traffic Violations on Unconstrained Roads
Aman Goyal, Dev Agarwal, Anbumani Subramanian +3
In many Asian countries with unconstrained road traffic conditions, driving violations such as not wearing helmets and triple-riding are a significant source of fatalities involvin…
Automatic Quantification and Visualization of Street Trees
Arpit Bahety, Rohit Saluja, Ravi Kiran Sarvadevabhatla +2
Assessing the number of street trees is essential for evaluating urban greenery and can help municipalities employ solutions to identify tree-starved streets. It can also help iden…
Meta Guided Metric Learner for Overcoming Class Confusion in Few-Shot Road Object Detection
Anay Majee, Anbumani Subramanian, Kshitij Agrawal
Localization and recognition of less-occurring road objects have been a challenge in autonomous driving applications due to the scarcity of data samples. Few-Shot Object Detection…
Multi-Domain Incremental Learning for Semantic Segmentation
Prachi Garg, Rohit Saluja, Vineeth N Balasubramanian +3
Recent efforts in multi-domain learning for semantic segmentation attempt to learn multiple geographical datasets in a universal, joint model. A simple fine-tuning experiment perfo…