2 citations · 5 across the 11 of their papers we have counts for
13 papers
ShlokaDhara: A Multi-Speaker Sanskrit Speech Corpus for Learning Meter-Aware Prosody in Text-to-Recitation
Harshal Kausadikar, Onkar Kishor Susladkar, Prathmesh Santosh Choudhari +4
Sanskrit verse recitation is governed by , a strict prosodic framework defined by rhythmic (light) and (heavy) syllables. Because…
Representations Have Trajectories: Characterizing Temporal Representation Dynamics in Neural Networks
Shivaprasad B. Gowda, Sparsh Mittal
Recent work has shown that deep neural networks exhibit an implicit low-rank simplicity bias. In this paper, we investigate the questions that naturally arise from this observation…
Best of Both Worlds: Multimodal Reasoning and Generation via Unified Discrete Flow Matching
Onkar Susladkar, Tushar Prakash, Gayatri Deshmukh +8
We propose UniDFlow, a unified discrete flow-matching framework for multimodal understanding, generation, and editing. It decouples understanding and generation via task-specific l…
Historic Scripts to Modern Vision: A Novel Dataset and A VLM Framework for Transliteration of Modi Script to Devanagari
Harshal Kausadikar, Tanvi Kale, Onkar Susladkar +1
In medieval India, the Marathi language was written using the Modi script. The texts written in Modi script include extensive knowledge about medieval sciences, medicines, land rec…
L2GNet: Optimal Local-to-Global Representation of Anatomical Structures for Generalized Medical Image Segmentation
Vandan Gorade, Sparsh Mittal, Neethi Dasu +3
Continuous Latent Space (CLS) and Discrete Latent Space (DLS) models, like AttnUNet and VQUNet, have excelled in medical image segmentation. In contrast, Synergistic Continuous and…
Dressing the Imagination: A Dataset for AI-Powered Translation of Text into Fashion Outfits and A Novel NeRA Adapter for Enhanced Feature Adaptation
Gayatri Deshmukh, Somsubhra De, Chirag Sehgal +2
Specialized datasets that capture the fashion industry's rich language and styling elements can boost progress in AI-driven fashion design. We present FLORA, (Fashion Language Outf…
MotionAura: Generating High-Quality and Motion Consistent Videos using Discrete Diffusion
Onkar Susladkar, Jishu Sen Gupta, Chirag Sehgal +2
The spatio-temporal complexity of video data presents significant challenges in tasks such as compression, generation, and inpainting. We present four key contributions to address…
Hybrid Quantum Neural Network based Indoor User Localization using Cloud Quantum Computing
Sparsh Mittal, Yash Chand, Neel Kanth Kundu
This paper proposes a hybrid quantum neural network (HQNN) for indoor user localization using received signal strength indicator (RSSI) values. We use publicly available RSSI datas…
D2Styler: Advancing Arbitrary Style Transfer with Discrete Diffusion Methods
Onkar Susladkar, Gayatri Deshmukh, Sparsh Mittal +1
In image processing, one of the most challenging tasks is to render an image's semantic meaning using a variety of artistic approaches. Existing techniques for arbitrary style tran…
Harmonized Spatial and Spectral Learning for Robust and Generalized Medical Image Segmentation
Vandan Gorade, Sparsh Mittal, Debesh Jha +2
Deep learning has demonstrated remarkable achievements in medical image segmentation. However, prevailing deep learning models struggle with poor generalization due to (i) intra-cl…
SPEEDNet: Salient Pyramidal Enhancement Encoder-Decoder Network for Colonoscopy Images
Tushir Sahu, Vidhi Bhatt, Sai Chandra Teja R +2
Accurate identification and precise delineation of regions of significance, such as tumors or lesions, is a pivotal goal in medical imaging analysis. This paper proposes SPEEDNet,…
Rethinking Intermediate Layers design in Knowledge Distillation for Kidney and Liver Tumor Segmentation
Vandan Gorade, Sparsh Mittal, Debesh Jha +1
Knowledge distillation (KD) has demonstrated remarkable success across various domains, but its application to medical imaging tasks, such as kidney and liver tumor segmentation, h…
SynergyNet: Bridging the Gap between Discrete and Continuous Representations for Precise Medical Image Segmentation
Vandan Gorade, Sparsh Mittal, Debesh Jha +1
In recent years, continuous latent space (CLS) and discrete latent space (DLS) deep learning models have been proposed for medical image analysis for improved performance. However,…