16 citations · 29 across the 21 of their papers we have counts for
17 papers · 1 filter
One Editor, Many Edits: A Unified Training-Free Framework for Diverse Video Editing
Adheesh Sunil Juvekar, Onkar Kishor Susladkar, Kiet A. Nguyen +6
Video editing spans diverse editing paradigms, yet achieving high-quality instruction-guided and subject-guided editing within a single unified framework remains challenging. We in…
ViTAL-X: Video-Text Alignment with Cross-Modal Temporal Edits
Sethuraman T, Savya Khosla, Onkar Kishor Susladkar +6
Video-text models adapted from image-text architectures (e.g., CLIP) frequently exhibit temporal blindness, the inability to perceive fundamental cues like order, direction, and mo…
GraphVid: Interactive Graph-Controllable Video Generation
Vedant Shah, Onkar Susladkar, Tushar Prakash +5
Controllable video generation remains challenging due to the difficulty of specifying precise multi-object interactions using text prompts or motion-control inputs that primarily c…
ELSA3D: Elastic Semantic Anchoring for Unified 3D Understanding and Generation
Tianjiao Yu, Xinzhuo Li, Yifan Shen +4
Unified 3D foundation models aspire to generate 3D assets and reason about them in language within a single backbone, but their text-3D interaction remains largely implicit. Existi…
RewardFlow: Generate Images by Optimizing What You Reward
Onkar Susladkar, Dong-Hwan Jang, Tushar Prakash +7
We introduce RewardFlow, an inversion-free framework that steers pretrained diffusion and flow-matching models at inference time through multi-reward Langevin dynamics. RewardFlow…
PyraTok: Language-Aligned Pyramidal Tokenizer for Video Understanding and Generation
Onkar Susladkar, Tushar Prakash, Adheesh Juvekar +4
Discrete video VAEs underpin modern text-to-video generation and video understanding systems, yet existing tokenizers typically learn visual codebooks at a single scale with limite…
Stress Tests REVEAL Fragile Temporal and Visual Grounding in Video-Language Models
Sethuraman T, Savya Khosla, Aditi Tiwari +12
Video-Language Models (VidLMs) achieve strong benchmark scores, yet these scores often hide whether models use the video at all. We show that VidLM failures follow two pathways: so…
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…
Pediatric Pancreas Segmentation from MRI Scans with Deep Learning
Elif Keles, Merve Yazol, Gorkem Durak +11
Objective: Our study aimed to evaluate and validate PanSegNet, a deep learning (DL) algorithm for pediatric pancreas segmentation on MRI in children with acute pancreatitis (AP), c…
ViCTr: Vital Consistency Transfer for Pathology Aware Image Synthesis
Onkar Susladkar, Gayatri Deshmukh, Yalcin Tur +2
Synthesizing medical images remains challenging due to limited annotated pathological data, modality domain gaps, and the complexity of representing diffuse pathologies such as liv…
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…
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…
Towards Synergistic Deep Learning Models for Volumetric Cirrhotic Liver Segmentation in MRIs
Vandan Gorade, Onkar Susladkar, Gorkem Durak +7
Liver cirrhosis, a leading cause of global mortality, requires precise segmentation of ROIs for effective disease monitoring and treatment planning. Existing segmentation models of…
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…
Show Me the World in My Language: Establishing the First Baseline for Scene-Text to Scene-Text Translation
Shreyas Vaidya, Arvind Kumar Sharma, Prajwal Gatti +1
In this work, we study the task of ``visually'' translating scene text from a source language (e.g., Hindi) to a target language (e.g., English). Visual translation involves not ju…
TPFNet: A Novel Text In-painting Transformer for Text Removal
Onkar Susladkar, Dhruv Makwana, Gayatri Deshmukh +3
Text erasure from an image is helpful for various tasks such as image editing and privacy preservation. In this paper, we present TPFNet, a novel one-stage (end-toend) network for…
ACLNet: An Attention and Clustering-based Cloud Segmentation Network
Dhruv Makwana, Subhrajit Nag, Onkar Susladkar +4
We propose a novel deep learning model named ACLNet, for cloud segmentation from ground images. ACLNet uses both deep neural network and machine learning (ML) algorithm to extract…