Anurag Ghosh

I'm a graduate student in the Computer Vision Group at Robotics Institute, Carnegie Mellon University, advised by Srinivasa Narasimhan and Christoph Mertz.

I spent a few wonderful years at Microsoft Research working at the intersection of Computer Vision and Networked/Distributed Systems for Social Good. I worked with Venkat Padmanabhan, Akshay Nambi and Tanuja Ganu.

I studied Computer Science at a vibrant and beautiful research-focused school, IIIT Hyderabad. I was advised by C. V. Jawahar and we worked on problems involving Computer Vision for Sports.

Here's my Resume.

Mentoring:If you would like to work with me, drop me an email with any specific finding you are excited by and why!

Email / GitHub / Google Scholar / LinkedIn

Research

I draw inspiration from sciences, and my ideas revolve around computer vision, machine learning, robotics and, systems. I'm learning about the geometric and physical structure of our world to augment next generations of computational intelligence.

	Learned Two-Plane Perspective Prior based Image Resampling for Efficient Object Detection Anurag Ghosh, N Dinesh Reddy, Christoph Mertz, Srinivasa Narasimhan Computer Vision and Pattern Recognition Conference(CVPR), 2023 [Website][Paper] A learnable geometry-guided prior that incorporates rough geometry of the 3D scene (a ground plane and a plane above) to resample the images for efficient object detection. This significantly improves small and far-away object detection performance while also being more efficient.
	Learning Runtime Decisions for Adaptive Real-Time Perception Anurag Ghosh, Akshay Nambi, Vaibhav Balloli, Aditya Singh, Tanuja Ganu Conference on Neural Information Processing Systems(NeurIPS), 2023 [Arxiv] Honorable Mention, Streaming Perception Challenge, CVPR 2021. [Presentation at WAD] Learning optimal tradeoffs instead of handcrafting heuristic functions is a more natural way to design complex real-time perception systems operating within severe resource constraints.
	Streaming Video Analytics On The Edge With Asynchronous Cloud Support Read about our work on Microsoft Research Blog! Anurag Ghosh, Srinivasan Iyengar, Stephen Lee, Anuj Rathore, Venkat Padmanabhan International Conference on Internet of Things Design and Implementation (IoTDI), 2023 [Paper] Should we choose between offloading and on-device execution for Edge AI workloads? Our simple algorithm shows that a careful combination of the two approaches makes them complementary and achieve state-of-the-art performance.
	Holistic Energy Awareness for Intelligent Drones Srinivasan Iyengar, Ravi Raj Saxena, Joydeep Pal, Bhawana Chhaglani, Anurag Ghosh, Venkat Padmanabhan, Prabhakar T. Venkata International Conference on Systems for Energy-Efficient Built Environments (ACM BuildSys), 2021 [Paper] (Best Paper Runner-Up) Holistically considering battery charecteristics and AI workload constraints for multi-drone flightpaths to develop an energy-aware scheduling system decreases energy consumed by 21.14% and mission times by 46.91% over state-of-the-art.
	Smartphone-based Driver License Testing Watch Microsoft CEO Satya Nadella explain the project! Read about our work on PM Awards Innovations Coffee Table Book! (Extracted here) Deployed in multiple states/10+ cities in India, automatically testing hundreds of thousands of drivers at a low-cost with >99% accuracy (test verified by human operator). See Overview and Dashboard. Instead of prohibitively expensive (>150,000$) overhead pole-mounted camera infrastructure to estimate car trajectories and judge driver manuevers, we use sub-500$ smartphones and additionally get driver state monitoring for free (face verification, mirror scanning, distraction and seatbelt checks). Relevant Publications [1] Smartphone-based Driver License Testing Anurag Ghosh, Vijay Lingam, Ishit Mehta, Akshay Nambi, Venkat Padmanabhan, Satish Sangameswaran, Conference on Embedded Networked Sensor Systems (ACM SenSys Demo), 2019 [Paper] [2] ALT: Towards Automating Driver License Testing using Smartphones Akshay Nambi, Ishit Mehta, Anurag Ghosh, Vijay Lingam, Venkat Padmanabhan, Conference on Embedded Networked Sensor Systems (ACM SenSys), 2019 [Paper]
	Analyzing Racket Sports From Broadcast Videos Piloted with ESPN/Star Sports at Premier Badminton League, watched by tens of millions in South East Asia. Do we really need half a million dollars for HawkEye to understand players? Our End-to-end framework automatically tags broadcast sport videos in near-real time. Our analysis shows a single camera suffices for mining rich and actionable player data, instead of relying on existing cumbursome multi-camera setups or sensors. It is used for live broadcast visualizations. Relevant Publications [1] Analyzing Racket Sports From Broadcast Videos Anurag Ghosh, IIIT Hyderabad (Master's Thesis), 2019 [Paper] [2] Towards Structured Analysis of Broadcast Badminton Videos Anurag Ghosh, Suriya Singh, C.V. Jawahar, Winter Conference On Applications of Computer Vision (WACV), 2018 [Paper] [3] SmartTennisTV: An automatic indexing system for tennis Anurag Ghosh, C.V. Jawahar, National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), 2017 [Paper] (Best Paper Award)
	Signals Matter: Understanding Popularity and Impact on Stack Overflow Arpit Merchant, Daksh Shah, Gurpreet Singh Bhatia, Anurag Ghosh, Ponnurangam Kumaraguru The Web Conference (WWW), 2019 [Paper]
	Dynamic narratives for heritage tour Anurag Ghosh , Yash Patel , Mohak Sukhwani, C.V. Jawahar VisArt Workshop, Europen Conference on Computer Vision (ECCV), 2016 [Paper]