activity
20162019
most citedGated-SCNN: Gated Shape CNNs for Semantic Segmentation

115 citations · 115 across the 1 of their papers we have counts for

collaborators

7 papers

cs.CV2019115 cited

Gated-SCNN: Gated Shape CNNs for Semantic Segmentation

Towaki Takikawa, David Acuna, Varun Jampani +1

Current state-of-the-art methods for image segmentation form a dense image representation where the color, shape and texture information are all processed together inside a deep CN…

cs.CV2019

SCOPS: Self-Supervised Co-Part Segmentation

Wei-Chih Hung, Varun Jampani, Sifei Liu +3

Parts provide a good intermediate representation of objects that is robust with respect to the camera, pose and appearance variations. Existing works on part segmentation is domina…

cs.CV2017

On the Integration of Optical Flow and Action Recognition

Laura Sevilla-Lara, Yiyi Liao, Fatma Guney +3

Most of the top performing action recognition methods use optical flow as a "black box" input. Here we take a deeper look at the combination of flow and action recognition, and inv…

cs.CV2017

Learning Inference Models for Computer Vision

Varun Jampani

Computer vision can be understood as the ability to perform inference on image data. Breakthroughs in computer vision technology are often marked by advances in inference technique…

cs.CV2017

Semantic Video CNNs through Representation Warping

Raghudeep Gadde, Varun Jampani, Peter V. Gehler

In this work, we propose a technique to convert CNN models for semantic segmentation of static images into CNNs for video data. We describe a warping method that can be used to aug…

cs.CV2016

Efficient 2D and 3D Facade Segmentation using Auto-Context

Raghudeep Gadde, Varun Jampani, Renaud Marlet +1

This paper introduces a fast and efficient segmentation technique for 2D images and 3D point clouds of building facades. Facades of buildings are highly structured and consequently…