10 citations · 16 across the 18 of their papers we have counts for
11 papers · 1 filter
Temporal Self-Distillation: Learning Visual State Tracking in Videos Without Supervision
Shravan Venkatraman, Wenshuai Zhao, Mohammad Hassan Vali +1
We introduce ST (Self-Supervised Self-Distillation over Time), which, to the best of our knowledge, is the first fully self-contained framework for continuous video state track…
Perception Before Supervision: Self-Contained Visual Distillation from Counterfactual Blind Spots
Shravan Venkatraman, Omkar Thawakar, Ritesh Thawkar +2
Self-improvement for multimodal large language models (MLLMs) is typically driven by reward-based methods that provide only coarse scalar feedback. Distillation offers a richer alt…
Ask, Solve, Generate: Self-Evolving Unified Multimodal Understanding and Generation via Self-Consistency Rewards
Ritesh Thawkar, Shravan Venkatraman, Omkar Thawakar +5
Most unified large multimodal models (LMMs) that support both visual understanding and image generation still rely on curated post-training supervision, such as human annotations,…
Paying More Attention to Visual Tokens in Self-Evolving Large Multimodal Models
Shravan Venkatraman, Ritesh Thawkar, Omkar Thawakar +4
Recently, self-evolving large multimodal models (LMMs) have received attention for improving visual reasoning in a purely unsupervised setting. However, multi-role self-play and se…
PCM-NeRF: Probabilistic Camera Modeling for Neural Radiance Fields under Pose Uncertainty
Shravan Venkatraman, Rakesh Raj Madavan, Pavan Kumar Sathya Venkatesh
Neural surface reconstruction methods typically treat camera poses as fixed values, assuming perfect accuracy from Structure-from-Motion (SfM) systems. This assumption breaks down…
TIDE: Two-Stage Inverse Degradation Estimation with Guided Prior Disentanglement for Underwater Image Restoration
Shravan Venkatraman, Rakesh Raj Madavan, Pavan Kumar S +1
Underwater image restoration is essential for marine applications ranging from ecological monitoring to archaeological surveys, but effectively addressing the complex and spatially…
Can We Go Beyond Visual Features? Neural Tissue Relation Modeling for Relational Graph Analysis in Non-Melanoma Skin Histology
Shravan Venkatraman, Muthu Subash Kavitha, Joe Dhanith P R +2
Histopathology image segmentation is essential for delineating tissue structures in skin cancer diagnostics, but modeling spatial context and inter-tissue relationships remains a c…
EvoLMM: Self-Evolving Large Multimodal Models with Continuous Rewards
Omkar Thawakar, Shravan Venkatraman, Ritesh Thawkar +5
Recent advances in large multimodal models (LMMs) have enabled impressive reasoning and perception abilities, yet most existing training pipelines still depend on human-curated dat…
FUSION: Frequency-guided Underwater Spatial Image recOnstructioN
Jaskaran Singh Walia, Shravan Venkatraman, Pavithra LK
Underwater images suffer from severe degradations, including color distortions, reduced visibility, and loss of structural details due to wavelength-dependent attenuation and scatt…
SAG-ViT: A Scale-Aware, High-Fidelity Patching Approach with Graph Attention for Vision Transformers
Shravan Venkatraman, Jaskaran Singh Walia, Joe Dhanith P R
Vision Transformers (ViTs) have redefined image classification by leveraging self-attention to capture complex patterns and long-range dependencies between image patches. However,…
A Channel Attention-Driven Hybrid CNN Framework for Paddy Leaf Disease Detection
Pandiyaraju V, Shravan Venkatraman, Abeshek A +4
Farmers face various challenges when it comes to identifying diseases in rice leaves during their early stages of growth, which is a major reason for poor produce. Therefore, early…