66 citations · 174 across the 32 of their papers we have counts for
37 papers
Local-Global Context-Aware and Structure-Preserving Image Super-Resolution
Sanchar Palit, Subhasis Chaudhuri, Biplab Banerjee
Diffusion models have recently achieved significant success in various image manipulation tasks, including image super-resolution and perceptual quality enhancement. Pretrained tex…
Revised Regularization for Efficient Continual Learning through Correlation-Based Parameter Update in Bayesian Neural Networks
Sanchar Palit, Biplab Banerjee, Subhasis Chaudhuri
We propose a Bayesian neural network-based continual learning algorithm using Variational Inference, aiming to overcome several drawbacks of existing methods. Specifically, in cont…
HAVE-Net: Hallucinated Audio-Visual Embeddings for Few-Shot Classification with Unimodal Cues
Ankit Jha, Debabrata Pal, Mainak Singha +2
Recognition of remote sensing (RS) or aerial images is currently of great interest, and advancements in deep learning algorithms added flavor to it in recent years. Occlusion, intr…
Efficient Curriculum based Continual Learning with Informative Subset Selection for Remote Sensing Scene Classification
S Divakar Bhat, Biplab Banerjee, Subhasis Chaudhuri +1
We tackle the problem of class incremental learning (CIL) in the realm of landcover classification from optical remote sensing (RS) images in this paper. The paradigm of CIL has re…
GOPro: Generate and Optimize Prompts in CLIP using Self-Supervised Learning
Mainak Singha, Ankit Jha, Biplab Banerjee
Large-scale foundation models, such as CLIP, have demonstrated remarkable success in visual recognition tasks by embedding images in a semantically rich space. Self-supervised lear…
Temporal DINO: A Self-supervised Video Strategy to Enhance Action Prediction
Izzeddin Teeti, Rongali Sai Bhargav, Vivek Singh +3
The emerging field of action prediction plays a vital role in various computer vision applications such as autonomous driving, activity analysis and human-computer interaction. Des…
AD-CLIP: Adapting Domains in Prompt Space Using CLIP
Mainak Singha, Harsh Pal, Ankit Jha +1
Although deep learning models have shown impressive performance on supervised learning tasks, they often struggle to generalize well when the training (source) and test (target) do…
Physically Plausible 3D Human-Scene Reconstruction from Monocular RGB Image using an Adversarial Learning Approach
Sandika Biswas, Kejie Li, Biplab Banerjee +2
Holistic 3D human-scene reconstruction is a crucial and emerging research area in robot perception. A key challenge in holistic 3D human-scene reconstruction is to generate a physi…
Visual Question Answering in Remote Sensing with Cross-Attention and Multimodal Information Bottleneck
Jayesh Songara, Shivam Pande, Shabnam Choudhury +2
In this research, we deal with the problem of visual question answering (VQA) in remote sensing. While remotely sensed images contain information significant for the task of identi…
Semi-Supervised Learning for hyperspectral images by non parametrically predicting view assignment
Shivam Pande, Nassim Ait Ali Braham, Yi Wang +3
Hyperspectral image (HSI) classification is gaining a lot of momentum in present time because of high inherent spectral information within the images. However, these images suffer…
USIM-DAL: Uncertainty-aware Statistical Image Modeling-based Dense Active Learning for Super-resolution
Vikrant Rangnekar, Uddeshya Upadhyay, Zeynep Akata +1
Dense regression is a widely used approach in computer vision for tasks such as image super-resolution, enhancement, depth estimation, etc. However, the high cost of annotation and…
APPLeNet: Visual Attention Parameterized Prompt Learning for Few-Shot Remote Sensing Image Generalization using CLIP
Mainak Singha, Ankit Jha, Bhupendra Solanki +2
In recent years, the success of large-scale vision-language models (VLMs) such as CLIP has led to their increased usage in various computer vision tasks. These models enable zero-s…
MultiScale Probability Map guided Index Pooling with Attention-based learning for Road and Building Segmentation
Shirsha Bose, Ritesh Sur Chowdhury, Debabrata Pal +3
Efficient road and building footprint extraction from satellite images are predominant in many remote sensing applications. However, precise segmentation map extraction is quite ch…
StyLIP: Multi-Scale Style-Conditioned Prompt Learning for CLIP-based Domain Generalization
Shirsha Bose, Ankit Jha, Enrico Fini +3
Large-scale foundation models, such as CLIP, have demonstrated impressive zero-shot generalization performance on downstream tasks, leveraging well-designed language prompts. Howev…
Prototypical quadruplet for few-shot class incremental learning
Sanchar Palit, Biplab Banerjee, Subhasis Chaudhuri
Scarcity of data and incremental learning of new tasks pose two major bottlenecks for many modern computer vision algorithms. The phenomenon of catastrophic forgetting, i.e., the m…
RSINet: Inpainting Remotely Sensed Images Using Triple GAN Framework
Advait Kumar, Dipesh Tamboli, Shivam Pande +1
We tackle the problem of image inpainting in the remote sensing domain. Remote sensing images possess high resolution and geographical variations, that render the conventional inpa…
BDA-SketRet: Bi-Level Domain Adaptation for Zero-Shot SBIR
Ushasi Chaudhuri, Ruchika Chavan, Biplab Banerjee +2
The efficacy of zero-shot sketch-based image retrieval (ZS-SBIR) models is governed by two challenges. The immense distributions-gap between the sketches and the images requires a…
FRIDA -- Generative Feature Replay for Incremental Domain Adaptation
Sayan Rakshit, Anwesh Mohanty, Ruchika Chavhan +3
We tackle the novel problem of incremental unsupervised domain adaptation (IDA) in this paper. We assume that a labeled source domain and different unlabeled target domains are inc…
Zero-Shot Sketch Based Image Retrieval using Graph Transformer
Sumrit Gupta, Ushasi Chaudhuri, Biplab Banerjee
The performance of a zero-shot sketch-based image retrieval (ZS-SBIR) task is primarily affected by two challenges. The substantial domain gap between image and sketch features nee…
A distillation based approach for the diagnosis of diseases
Hmrishav Bandyopadhyay, Shuvayan Ghosh Dastidar, Bisakh Mondal +2
Presently, Covid-19 is a serious threat to the world at large. Efforts are being made to reduce disease screening times and in the development of a vaccine to resist this disease,…
Two Headed Dragons: Multimodal Fusion and Cross Modal Transactions
Rupak Bose, Shivam Pande, Biplab Banerjee
As the field of remote sensing is evolving, we witness the accumulation of information from several modalities, such as multispectral (MS), hyperspectral (HSI), LiDAR etc. Each of…
Federated Action Recognition on Heterogeneous Embedded Devices
Pranjal Jain, Shreyas Goenka, Saurabh Bagchi +2
Federated learning allows a large number of devices to jointly learn a model without sharing data. In this work, we enable clients with limited computing power to perform action re…
CrossATNet - A Novel Cross-Attention Based Framework for Sketch-Based Image Retrieval
Ushasi Chaudhuri, Biplab Banerjee, Avik Bhattacharya +1
We propose a novel framework for cross-modal zero-shot learning (ZSL) in the context of sketch-based image retrieval (SBIR). Conventionally, the SBIR schema mainly considers simult…
Trusting small training dataset for supervised change detection
Sudipan Saha, Biplab Banerjee, Xiao Xiang Zhu
Deep learning (DL) based supervised change detection (CD) models require large labeled training data. Due to the difficulty of collecting labeled multi-temporal data, unsupervised…