Anurag GhoshI'm a Robotics PhD at Carnegie Mellon, advised by Srinivasa Narasimhan working on Computer Vision and Imaging problems. I was co-advised by Srinivasa Narasimhan and Christoph Mertz when I got my Masters here. 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. Even earlier, I studied 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 |
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ResearchI love building intelligent systems that work. To do so, I draw inspiration from natural sciences, and my work revolves around developing novel algorithms and applications of computer vision, machine learning, robotics and, systems. |
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AerialMegaDepth: Learning Aerial-Ground Reconstruction and View Synthesis Khiem Vuong, Anurag Ghosh, Deva Ramanan*, Srinivasa Narasimhan*, Shubham Tulsiani*Conference on Computer Vision and Pattern Recognition(CVPR), 2025 [Website][Paper][Code] A scalable data generation framework that combines mesh-renderings with real images, enabling robust 3D reconstruction across extreme viewpoint variations (e.g., aerial-ground). |
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ROADWork Dataset: Learning to Recognize, Observe, Analyze and Drive Through Work Zones Anurag Ghosh, Robert Tamburo, Shen Zheng, Juan R. Alvarez Padilla, Hailiang Zhu, Michael Cardei, Nicholas Dunn, Christoph Mertz, Srinivasa Narasimhan[Website][Paper][Code] Largest open-source dataset for studying autonomous driving in work zones. |
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Saliency Guided Image Warping for Unsupervised Domain Adaptation Shen Zheng★, Anurag Ghosh★, Srinivasa NarasimhanWinter Conference on Applications of Computer Vision(WACV), 2025 [Website][Paper][Code] Oversample salient object regions by warping source-domain images in-place during training while performing domain adaptation. Improve adaptation across geographies, lighting and weather conditions, is agnostic to the task, domain adaptation algorithm, saliency guidance, and underlying model architecture. |
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Learned Two-Plane Perspective Prior based Image Resampling for Efficient Object Detection Anurag Ghosh, N Dinesh Reddy, Christoph Mertz, Srinivasa NarasimhanConference on Computer Vision and Pattern Recognition(CVPR), 2023 [Website][Paper][Code] 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. |
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Exploiting Tradeoffs in Resource Constrained Vision Novel methods for improving trade-offs at different levels of vision system abstractions. We considered constraints like real-timeness, network latency/bandwidth, inter-process contention, onboard compute, power, heat and battery considerations. Relevant Publications[1] Chanakya: Learning Runtime Decisions for Adaptive Real-Time PerceptionAnurag Ghosh, Vaibhav Balloli, Akshay Nambi, Aditya Singh, Tanuja Ganu Conference on Neural Information Processing Systems(NeurIPS), 2023 [Website][Paper][Code] Honorable Mention, Streaming Perception Challenge, CVPR 2021. [Presentation at WAD] [2] REACT: Streaming Video Analytics On The Edge With Asynchronous Cloud Support Anurag Ghosh, Srinivasan Iyengar, Stephen Lee, Anuj Rathore, Venkat Padmanabhan International Conference on Internet of Things Design and Implementation (IoTDI), 2023 [Paper] [3] 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 (BuildSys), 2021 [Paper] (Best Paper Runner-Up) (Also appeared in Transactions on Sensor Networks) |
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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 TestingAnurag Ghosh, Vijay Lingam, Ishit Mehta, Akshay Nambi, Venkat Padmanabhan, Satish Sangameswaran, Conference on Embedded Networked Sensor Systems (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 (SenSys), 2019 [Paper] |
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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 VideosAnurag 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) |
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Signals Matter: Understanding Popularity and Impact on Stack Overflow Arpit Merchant, Daksh Shah, Gurpreet Singh Bhatia, Anurag Ghosh, Ponnurangam KumaraguruThe Web Conference (WWW), 2019 [Paper] |
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Dynamic narratives for heritage tour Anurag Ghosh ★, Yash Patel ★, Mohak Sukhwani, C.V. JawaharVisArt Workshop, Europen Conference on Computer Vision (ECCV), 2016 [Paper] |
Press |
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Automated Driver License Testing |
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Badminton Analytics |
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Interesting/Inspiring Links |
Making computer vision systems that work: Boujou, Kinect, HoloLens, Andrew Fitzgibbon |
A New Kind of Science - A 15 Year View, Stephen Wolfram |
How I ran the length of every street in Pittsburgh: PAC TOM, Tom Murphy VII |
Frugal Innovations for a Developing World, Bill Thies |
Hints and Principles for Computer System Design, Butler Lampson |
The Advent of Actionable Tennis Analytics, Jeff Sackmann |
Automatic Pool Stick vs Strangers, Shane Wighton |
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I must study Politicks and War that my sons may have liberty to study Mathematicks and Philosophy. My sons ought to study Mathematicks and Philosophy, Geography, natural History, Naval Architecture, navigation, Commerce and Agriculture, in order to give their Children a right to study Painting, Poetry, Musick, Architecture, Statuary, Tapestry and Porcelaine. - John Adams, American Founding Father |
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Design and source code from Jon Barron's website |