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Visesh Chari on Muck Rack

Visesh Chari

As seen in: Amazon Science
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Articles

Towards accurate 3D human body reconstruction from silhouettes

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By Brandon Smith Verified, Amit Agrawal, James M. Rehg, Visesh Chari
| Amazon Science
Take Earth's most customer-centric company. Mix in hundreds of millions of shoppers spending tens of billions of dollars annually, an exciting opportunity to build next-generation shopping experiences, Amazon’s tremendous computational resources, and our extensive e-Commerce experience. What do you get? The most exciting position in the industry. Amazon’s Personalization team is looking for a Principal Applied Scientist to lead step function science improvements across the recommendations space.
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Multi-instance pose networks: Rethinking top down pose estimation

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By Rawal Khirodkar, Visesh Chari, Amit Agrawal, Ambrish Tyagi
| Amazon Science
A key assumption of top-down human pose estimation approaches is their expectation of having a single person/instance present in the input bounding box. This often leads to failures in crowded scenes with occlusions. We propose a novel solution to overcome the limitations of this fundamental assumption. Our Multi-Instance Pose Network (MIPNet) allows for predicting multiple 2D pose instances within a given bounding box.
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