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Visesh Chari

7 accepted papers

2021

Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation

ICCV 2021poster

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 assumpt…

Cited by 99PDF ↗code ↗Scholar ↗
2019

Learning to Generate Synthetic Data via Compositing

CVPR 2019poster

We present a task-specific approach to synthetic data generation. Our framework employs a trainable synthesizer network that is optimized to produce meaningful training samples by assessing the strengths and weaknesses of a 'target' classifier. The synthesizer and target networks are trained in an a…

Cited by 169PDF ↗Scholar ↗
2016

Monocular reconstruction of vehicles: Combining SLAM with shape priors

ICRA 2016

Reasoning about objects in images and videos using 3D representations is re-emerging as a popular paradigm in computer vision. Specifically, in the context of scene understanding for roads, 3D vehicle detection and tracking from monocular videos still needs a lot of attention to enable practical app

Cited by 50Source ↗Scholar ↗
2016

Rolling shutter and motion blur removal for depth cameras

ICRA 2016

Structured light range sensors (SLRS) like the Microsoft Kinect have electronic rolling shutters (ERS). The output of such a sensor while in motion is subject to significant motion blur (MB) and rolling shutter (RS) distortion. Most robotic literature still does not explicitly model this distortion,

Cited by 10Source ↗Scholar ↗
2015

On Pairwise Costs for Network Flow Multi-Object Tracking

CVPR 2015poster

Multi-object tracking has been recently approached with the min-cost network flow optimization techniques. Such methods simultaneously resolve multiple object tracks in a video and enable modeling of dependencies among tracks. Min-cost network flow methods also fit well within the "tracking-by-detec…

Cited by 164Source ↗PDF ↗Scholar ↗