Search Results for author: Bhabatosh Chanda

Found 12 papers, 3 papers with code

Significance of Anatomical Constraints in Virtual Try-On

no code implementations4 Jan 2024 Debapriya Roy, Sanchayan Santra, Diganta Mukherjee, Bhabatosh Chanda

In general, a VTON system takes a clothing source and a person's image to predict the try-on output of the person in the given clothing.

Anatomy Virtual Try-on

Significance of Skeleton-based Features in Virtual Try-On

no code implementations17 Aug 2022 Debapriya Roy, Sanchayan Santra, Diganta Mukherjee, Bhabatosh Chanda

The idea of \textit{Virtual Try-ON} (VTON) benefits e-retailing by giving an user the convenience of trying a clothing at the comfort of their home.

Virtual Try-on

An Unsupervised Approach towards Varying Human Skin Tone Using Generative Adversarial Networks

no code implementations30 Oct 2020 Debapriya Roy, Diganta Mukherjee, Bhabatosh Chanda

Given any input image of a person or a group of persons with some value indicating the desired change of skin color towards fairness or darkness, this method can change the skin tone of the persons in the image.

Attribute Fairness

LGVTON: A Landmark Guided Approach to Virtual Try-On

no code implementations1 Apr 2020 Debapriya Roy, Sanchayan Santra, Bhabatosh Chanda

In the first stage, LGVTON warps the clothes of the model using a Thin-Plate Spline (TPS) based transformation to fit the person.

SSIM Virtual Try-on

Morphological Networks for Image De-raining

1 code implementation8 Jan 2019 Ranjan Mondal, Pulak Purkait, Sanchayan Santra, Bhabatosh Chanda

Mathematical morphological methods have successfully been applied to filter out (emphasize or remove) different structures of an image.

SSIM

Morphological Network: How Far Can We Go with Morphological Neurons?

no code implementations ICLR 2019 Ranjan Mondal, Sanchayan Santra, Soumendu Sundar Mukherjee, Bhabatosh Chanda

A few works have tried to utilize morphological neurons as a part of classification (and regression) networks when the input is a feature vector.

 Ranked #1 on Representation Learning on Circle Data (using extra training data)

Image Dehazing regression +2

Reconstruction Loss Minimized FCN for Single Image Dehazing

no code implementations27 Nov 2018 Shirsendu Sukanta Halder, Sanchayan Santra, Bhabatosh Chanda

In this paper, we propose a Fully Convolutional Neural Network based model to recover the clear scene radiance by estimating the environmental illumination and the scene transmittance jointly from a hazy image.

Image Dehazing Single Image Dehazing

Local Jet Pattern: A Robust Descriptor for Texture Classification

no code implementations26 Nov 2017 Swalpa Kumar Roy, Bhabatosh Chanda, Bidyut. B. Chaudhuri, Dipak Kumar Ghosh, Shiv Ram Dubey

In this approach, a jet space representation of a texture image is derived from a set of derivatives of Gaussian (DtGs) filter responses up to second order, so called local jet vectors (LJV), which also satisfy the Scale Space properties.

Classification General Classification +1

Fractal image compression using upper bound on scaling parameter

1 code implementation14 Nov 2017 Swalpa Kumar Roy, Siddharth Kumar, Bhabatosh Chanda, Bidyut. B. Chaudhuri, Soumitro Banerjee

This paper presents a novel approach to calculate the affine parameters of fractal encoding, in order to reduce its computational complexity.

Image Compression

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