I am a Ph.D. candidate at The Robotics Institute, Carnegie Mellon University advised by Prof. Deva Ramanan. My research focus is broadly on spatiotemporal 4D scene understanding and its applications. Previously, I did my Masters in Robotics at CMU and Bachelors in Computer Engineering at University of Delhi. I have had the fortune to work at amazing companies - Boston Dynamics AI Institute, Google Research, Argo AI, Staqu Technologies.

I am a trained Kathak dancer, and Hindustani classical vocalist. I love baking, taking care of plants, and hiking. My life is made easier by my husband, Akash Sharma, who does research in robotics.

[03/24] We launched the 2nd iteration of Argoverse2.0 Occupancy Forecasting Challenge.
[02/24] I'll be at the Boston Dynamics AI Institute this summer.
[08/23] I was chosen as a Rising Star in EECS!
[07/23] I gave a talk on building 4D foundation models at Waabi AI.
[06/23] We are all set to organize the Argoverse2.0 Challenges at CVPR 2023!
[03/23] Our work on 4D occupancy forecasting was accepted to CVPR 2023!
[07/22] Detecting Invisible People was covered by NBC Universal.
[01/22] I'll be at Google Research this summer, working with Alireza Fathi and Cordelia Schmid!
[07/21] My favorite work, Detecting Invisible People, was accepted to ICCV '21!
[04/21] I accepted CMU's PhD offer for Fall '21.

CV   /   Google Scholar   /   tarasha@cmu.edu

	Using Diffusion Priors for Video Amodal Segmentation Kaihua Chen, Deva Ramanan, Tarasha Khurana In submission. [pdf] [project page] [code (coming soon)]
	Predicting Long-horizon Futures by Conditioning on Geometry and Time Tarasha Khurana, Deva Ramanan arXiv preprint arXiv:2404.11554, 2024. [pdf] [project page]
	TAO-Amodal: A Benchmark for Tracking any Object Amodally Cheng-Yen Hseih, Kaihua Chen, Achal Dave, Tarasha Khurana, Deva Ramanan In submission. [pdf] [project page] [code]
	Point Cloud Forecasting as a Proxy for 4D Occupancy Forecasting Tarasha Khurana, Peiyun Hu, David Held, Deva Ramanan IEEE/CVF Conferece on Computer Vision and Pattern Recognition (CVPR), '23. [pdf] [project page] [code]
	Differentiable Raycasting for Self-supervised Planning Tarasha Khurana*, Peiyun Hu*, Achal Dave, Jason Ziglar, David Held, Deva Ramanan European Conference on Computer Vision (ECCV), '22. [pdf] [project page] [code]
	BURST: A Benchmark for Unifying Object Recognition, Segmentation and Tracking in Videos Ali Athar, Jonathon Luiten, Paul Voigtlaender, Tarasha Khurana, Achal Dave, Bastian Leibe, Deva Ramanan IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023. [arXiv] [benchmark & API]
	Detecting Invisible People Tarasha Khurana, Achal Dave, Deva Ramanan International Conference on Computer Vision (ICCV), '21. [arXiv] [project page] [code]
	Detecting Invisible People's media coverage by NBC Universal. [article]
	TAO: A Large-Scale Benchmark for Tracking Any Object Achal Dave, Tarasha Khurana, Pavel Tokmakov, Cordelia Schmid, Deva Ramanan European Conference on Computer Vision (ECCV) '20. Spotlight. [arXiv] [project page] [workshop] [dataset]
	Exploiting Texture Cues for Clothing Parsing in Fashion Images Tarasha Khurana, Kushagra Mahajan, Chetan Arora, Atul Rai 25th IEEE International Conference on Image Processing (ICIP) '18. [pdf] [poster] [Xplore]
	Pose Aware Fine Grained Visual Classification Using Pose Experts Kushagra Mahajan, Tarasha Khurana, Ayush Chopra, Isha Gupta, Chetan Arora, Atul Rai 25th IEEE International Conference on Image Processing (ICIP) '18. [pdf] [poster] [Xplore]