R. Venkatesh Babu

research

∙ 09/14/2023

CoRF : Colorizing Radiance Fields using Knowledge Distillation

Neural radiance field (NeRF) based methods enable high-quality novel-vie...

0 Ankit Dhiman, et al. ∙

research

∙ 08/27/2023

Domain-Specificity Inducing Transformers for Source-Free Domain Adaptation

Conventional Domain Adaptation (DA) methods aim to learn domain-invarian...

0 Sunandini Sanyal, et al. ∙

research

∙ 08/20/2023

Strata-NeRF : Neural Radiance Fields for Stratified Scenes

Neural Radiance Field (NeRF) approaches learn the underlying 3D represen...

0 Ankit Dhiman, et al. ∙

research

∙ 06/10/2023

Boosting Adversarial Robustness using Feature Level Stochastic Smoothing

Advances in adversarial defenses have led to a significant improvement i...

0 Sravanti Addepalli, et al. ∙

research

∙ 06/01/2023

We never go out of Style: Motion Disentanglement by Subspace Decomposition of Latent Space

Real-world objects perform complex motions that involve multiple indepen...

0 Raghav Magazine, et al. ∙

research

∙ 05/18/2023

Inspecting the Geographical Representativeness of Images from Text-to-Image Models

Recent progress in generative models has resulted in models that produce...

0 Abhipsa Basu, et al. ∙

research

∙ 04/20/2023

Certified Adversarial Robustness Within Multiple Perturbation Bounds

Randomized smoothing (RS) is a well known certified defense against adve...

0 Soumalya Nandi, et al. ∙

research

∙ 04/15/2023

Continual Domain Adaptation through Pruning-aided Domain-specific Weight Modulation

In this paper, we propose to develop a method to address unsupervised do...

0 Prasanna B, et al. ∙

research

∙ 04/12/2023

NoisyTwins: Class-Consistent and Diverse Image Generation through StyleGANs

StyleGANs are at the forefront of controllable image generation as they ...

0 Harsh Rangwani, et al. ∙

research

∙ 04/01/2023

CapsFlow: Optical Flow Estimation with Capsule Networks

We present a framework to use recently introduced Capsule Networks for s...

3 Rahul Chand, et al. ∙

research

∙ 03/27/2023

Few-Shot Domain Adaptation for Low Light RAW Image Enhancement

Enhancing practical low light raw images is a difficult task due to seve...

0 K. Ram Prabhakar, et al. ∙

research

∙ 02/28/2023

DART: Diversify-Aggregate-Repeat Training Improves Generalization of Neural Networks

Generalization of neural networks is crucial for deploying them safely i...

0 Samyak Jain, et al. ∙

research

∙ 12/28/2022

Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data

Real-world datasets exhibit imbalances of varying types and degrees. Sev...

9 Harsh Rangwani, et al. ∙

research

∙ 10/28/2022

Subsidiary Prototype Alignment for Universal Domain Adaptation

Universal Domain Adaptation (UniDA) deals with the problem of knowledge ...

0 Jogendra Nath Kundu, et al. ∙

research

∙ 10/27/2022

Efficient and Effective Augmentation Strategy for Adversarial Training

Adversarial training of Deep Neural Networks is known to be significantl...

0 Sravanti Addepalli, et al. ∙

research

∙ 10/18/2022

Towards Efficient and Effective Self-Supervised Learning of Visual Representations

Self-supervision has emerged as a propitious method for visual represent...

0 Sravanti Addepalli, et al. ∙

research

∙ 10/18/2022

Scaling Adversarial Training to Large Perturbation Bounds

The vulnerability of Deep Neural Networks to Adversarial Attacks has fue...

0 Sravanti Addepalli, et al. ∙

research

∙ 10/04/2022

Learning an Invertible Output Mapping Can Mitigate Simplicity Bias in Neural Networks

Deep Neural Networks are known to be brittle to even minor distribution ...

5 Sravanti Addepalli, et al. ∙

research

∙ 08/21/2022

Improving GANs for Long-Tailed Data through Group Spectral Regularization

Deep long-tailed learning aims to train useful deep networks on practica...

5 Harsh Rangwani, et al. ∙

research

∙ 08/07/2022

Hierarchical Semantic Regularization of Latent Spaces in StyleGANs

Progress in GANs has enabled the generation of high-resolution photoreal...

8 Tejan Karmali, et al. ∙

research

∙ 07/27/2022

Concurrent Subsidiary Supervision for Unsupervised Source-Free Domain Adaptation

The prime challenge in unsupervised domain adaptation (DA) is to mitigat...

0 Jogendra Nath Kundu, et al. ∙

research

∙ 07/20/2022

Everything is There in Latent Space: Attribute Editing and Attribute Style Manipulation by StyleGAN Latent Space Exploration

Unconstrained Image generation with high realism is now possible using r...

0 Ankit Dhiman, et al. ∙

research

∙ 07/04/2022

Segmentation Guided Deep HDR Deghosting

We present a motion segmentation guided convolutional neural network (CN...

0 K. Ram Prabhakar, et al. ∙

research

∙ 06/16/2022

A Closer Look at Smoothness in Domain Adversarial Training

Domain adversarial training has been ubiquitous for achieving invariant ...

6 Harsh Rangwani, et al. ∙

research

∙ 06/16/2022

Balancing Discriminability and Transferability for Source-Free Domain Adaptation

Conventional domain adaptation (DA) techniques aim to improve domain tra...

3 Jogendra Nath Kundu, et al. ∙

research

∙ 04/23/2022

Towards Data-Free Model Stealing in a Hard Label Setting

Machine learning models deployed as a service (MLaaS) are susceptible to...

0 Sunandini Sanyal, et al. ∙

research

∙ 04/06/2022

LEAD: Self-Supervised Landmark Estimation by Aligning Distributions of Feature Similarity

In this work, we introduce LEAD, an approach to discover landmarks from ...

3 Tejan Karmali, et al. ∙

research

∙ 04/05/2022

Non-Local Latent Relation Distillation for Self-Adaptive 3D Human Pose Estimation

Available 3D human pose estimation approaches leverage different forms o...

0 Jogendra Nath Kundu, et al. ∙

research

∙ 04/04/2022

Aligning Silhouette Topology for Self-Adaptive 3D Human Pose Recovery

Articulation-centric 2D/3D pose supervision forms the core training obje...

0 Mugalodi Rakesh, et al. ∙

research

∙ 03/29/2022

Uncertainty-Aware Adaptation for Self-Supervised 3D Human Pose Estimation

The advances in monocular 3D human pose estimation are dominated by supe...

0 Jogendra Nath Kundu, et al. ∙

research

∙ 02/09/2022

Amplitude Spectrum Transformation for Open Compound Domain Adaptive Semantic Segmentation

Open compound domain adaptation (OCDA) has emerged as a practical adapta...

0 Jogendra Nath Kundu, et al. ∙

research

∙ 12/24/2021

Self-Gated Memory Recurrent Network for Efficient Scalable HDR Deghosting

We propose a novel recurrent network-based HDR deghosting method for fus...

6 K. Ram Prabhakar, et al. ∙

research

∙ 09/18/2021

S^3VAADA: Submodular Subset Selection for Virtual Adversarial Active Domain Adaptation

Unsupervised domain adaptation (DA) methods have focused on achieving ma...

5 Harsh Rangwani, et al. ∙

research

∙ 08/25/2021

Generalize then Adapt: Source-Free Domain Adaptive Semantic Segmentation

Unsupervised domain adaptation (DA) has gained substantial interest in s...

15 Jogendra Nath Kundu, et al. ∙

research

∙ 06/17/2021

Class Balancing GAN with a Classifier in the Loop

Generative Adversarial Networks (GANs) have swiftly evolved to imitate i...

10 Harsh Rangwani, et al. ∙

research

∙ 03/20/2021

Your Classifier can Secretly Suffice Multi-Source Domain Adaptation

Multi-Source Domain Adaptation (MSDA) deals with the transfer of task kn...

1 Naveen Venkat, et al. ∙

research

∙ 11/30/2020

Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses

Advances in the development of adversarial attacks have been fundamental...

0 Gaurang Sriramanan, et al. ∙

research

∙ 09/14/2020

Completely Self-Supervised Crowd Counting via Distribution Matching

Dense crowd counting is a challenging task that demands millions of head...

2 Deepak Babu Sam, et al. ∙

research

∙ 08/04/2020

Class-Incremental Domain Adaptation

We introduce a practical Domain Adaptation (DA) paradigm called Class-In...

22 Jogendra Nath Kundu, et al. ∙

research

∙ 08/04/2020

Unsupervised Cross-Modal Alignment for Multi-Person 3D Pose Estimation

We present a deployment friendly, fast bottom-up framework for multi-per...

1 Jogendra Nath Kundu, et al. ∙

research

∙ 08/04/2020

Appearance Consensus Driven Self-Supervised Human Mesh Recovery

We present a self-supervised human mesh recovery framework to infer huma...

0 Jogendra Nath Kundu, et al. ∙

research

∙ 08/03/2020

Fusion of Deep and Non-Deep Methods for Fast Super-Resolution of Satellite Images

In the emerging commercial space industry there is a drastic increase in...

20 Gaurav Kumar Nayak, et al. ∙

research

∙ 07/31/2020

Saliency-driven Class Impressions for Feature Visualization of Deep Neural Networks

In this paper, we propose a data-free method of extracting Impressions o...

9 Sravanti Addepalli, et al. ∙

research

∙ 07/07/2020

Learning to Count in the Crowd from Limited Labeled Data

Recent crowd counting approaches have achieved excellent performance. ho...

6 Vishwanath A. Sindagi, et al. ∙

research

∙ 06/24/2020

Kinematic-Structure-Preserved Representation for Unsupervised 3D Human Pose Estimation

Estimation of 3D human pose from monocular image has gained considerable...

0 Jogendra Nath Kundu, et al. ∙

research

∙ 05/05/2020

From Image Collections to Point Clouds with Self-supervised Shape and Pose Networks

Reconstructing 3D models from 2D images is one of the fundamental proble...

18 K L Navaneet, et al. ∙

research

∙ 04/27/2020

Adversarial Fooling Beyond "Flipping the Label"

Recent advancements in CNNs have shown remarkable achievements in variou...

0 Konda Reddy Mopuri, et al. ∙

research

∙ 04/18/2020

Single-step Adversarial training with Dropout Scheduling

Deep learning models have shown impressive performance across a spectrum...

0 Vivek B. S., et al. ∙

research

∙ 04/09/2020

Self-Supervised 3D Human Pose Estimation via Part Guided Novel Image Synthesis

Camera captured human pose is an outcome of several sources of variation...

0 Jogendra Nath Kundu, et al. ∙

research

∙ 04/09/2020

Universal Source-Free Domain Adaptation

There is a strong incentive to develop versatile learning techniques tha...

26 Jogendra Nath Kundu, et al. ∙

R. Venkatesh Babu

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