Search Results for author: Raghudeep Gadde

Found 10 papers, 2 papers with code

Network-Free, Unsupervised Semantic Segmentation With Synthetic Images

no code implementations CVPR 2023 Qianli Feng, Raghudeep Gadde, Wentong Liao, Eduard Ramon, Aleix Martinez

We derive a method that yields highly accurate semantic segmentation maps without the use of any additional neural network, layers, manually annotated training data, or supervised training.

Segmentation Unsupervised Semantic Segmentation

Near Perfect GAN Inversion

no code implementations23 Feb 2022 Qianli Feng, Viraj Shah, Raghudeep Gadde, Pietro Perona, Aleix Martinez

To edit a real photo using Generative Adversarial Networks (GANs), we need a GAN inversion algorithm to identify the latent vector that perfectly reproduces it.

Rayleigh EigenDirections (REDs): GAN latent space traversals for multidimensional features

no code implementations25 Jan 2022 Guha Balakrishnan, Raghudeep Gadde, Aleix Martinez, Pietro Perona

We present a method for finding paths in a deep generative model's latent space that can maximally vary one set of image features while holding others constant.

Semantic Video CNNs through Representation Warping

1 code implementation ICCV 2017 Raghudeep Gadde, Varun Jampani, Peter V. Gehler

A key insight of this work is that fast optical flow methods can be combined with many different CNN architectures for improved performance and end-to-end training.

Optical Flow Estimation Semantic Segmentation

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

no code implementations21 Jun 2016 Raghudeep Gadde, Varun Jampani, Renaud Marlet, Peter V. Gehler

This paper introduces a fast and efficient segmentation technique for 2D images and 3D point clouds of building facades.

Segmentation

Superpixel Convolutional Networks using Bilateral Inceptions

1 code implementation20 Nov 2015 Raghudeep Gadde, Varun Jampani, Martin Kiefel, Daniel Kappler, Peter V. Gehler

We introduce a new 'bilateral inception' module that can be inserted in existing CNN architectures and performs bilateral filtering, at multiple feature-scales, between superpixels in an image.

Image Segmentation Segmentation +2

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