5 papers · 1 filter
Prompt, Probe, Train, or Annotate? Single-camera sports video understanding in amateur settings
Sai Varun Kodathala, Prashanth Pollishetty, Jaylen Cargill
Video understanding is usually benchmarked on curated, single-actor, or professionally filmed clips, and a strong score there is routinely read as evidence a model is robust enough…
Temporal vs. Spatial: Comparing DINOv3 and V-JEPA2 Feature Representations for Video Action Analysis
Sai Varun Kodathala, Rakesh Vunnam
This study presents a comprehensive comparative analysis of two prominent self-supervised learning architectures for video action recognition: DINOv3, which processes frames indepe…
Fast OTSU Thresholding Using Bisection Method
Sai Varun Kodathala
The Otsu thresholding algorithm represents a fundamental technique in image segmentation, yet its computational efficiency is severely limited by exhaustive search requirements acr…
The Describe-Then-Generate Bottleneck: How VLM Descriptions Alter Image Generation Outcomes
Sai Varun Kodathala, Rakesh Vunnam
With the increasing integration of multimodal AI systems in creative workflows, understanding information loss in vision-language-vision pipelines has become important for evaluati…
SV3.3B: A Sports Video Understanding Model for Action Recognition
Sai Varun Kodathala, Yashwanth Reddy Vutukoori, Rakesh Vunnam
This paper addresses the challenge of automated sports video analysis, which has traditionally been limited by computationally intensive models requiring server-side processing and…