3 citations · 4 across the 8 of their papers we have counts for
10 papers
SlotAVS: Object-Centric Audio-Visual Segmentation via Bi-Modal Slot Attention
Arnav Sharma, Anand Mishra, Renu Rameshan
Audio-Visual Segmentation (AVS) requires predicting pixel-wise masks of sounding objects by grounding acoustic signals in visual space. In multi-source scenes, concurrent sound sou…
Robust Representation Learning in Masked Autoencoders
Anika Shrivastava, Renu Rameshan, Samar Agnihotri
Masked Autoencoders (MAEs) achieve impressive performance in image classification tasks, yet the internal representations they learn remain less understood. This work started as an…
Latent Space Characterization of Autoencoder Variants
Anika Shrivastava, Renu Rameshan, Samar Agnihotri
Understanding the latent spaces learned by deep learning models is crucial in exploring how they represent and generate complex data. Autoencoders (AEs) have played a key role in t…
Lossless Image Compression Using Multi-level Dictionaries: Binary Images
Samar Agnihotri, Renu Rameshan, Ritwik Ghosal
Lossless image compression is required in various applications to reduce storage or transmission costs of images, while requiring the reconstructed images to have zero information…
Simulation of a Vision Correction Display System
Vidya Sunil, Renu M Rameshan
Eyes serve as our primary sensory organs, responsible for processing up to 80\% of our sensory input. However, common visual aberrations like myopia and hyperopia affect a signific…
Analysis of Learned Features and Framework for Potato Disease Detection
Shikha Gupta, Soma Chakraborty, Renu Rameshan
For applications like plant disease detection, usually, a model is trained on publicly available data and tested on field data. This means that the test data distribution is not th…
G-PECNet: Towards a Generalizable Pedestrian Trajectory Prediction System
Aryan Garg, Renu M. Rameshan
Navigating dynamic physical environments without obstructing or damaging human assets is of quintessential importance for social robots. In this work, we solve autonomous drone nav…
Learning-Based Practical Light Field Image Compression Using A Disparity-Aware Model
Mohana Singh, Renu M. Rameshan
Light field technology has increasingly attracted the attention of the research community with its many possible applications. The lenslet array in commercial plenoptic cameras hel…
Learning optimally separated class-specific subspace representations using convolutional autoencoder
Krishan Sharma, Shikha Gupta, Renu Rameshan
In this work, we propose a novel convolutional autoencoder based architecture to generate subspace specific feature representations that are best suited for classification task. Th…
MOTS R-CNN: Cosine-margin-triplet loss for multi-object tracking
Amit Satish Unde, Renu M. Rameshan
One of the central tasks of multi-object tracking involves learning a distance metric that is consistent with the semantic similarities of objects. The design of an appropriate los…