*Disclaimer: A generous participant of our sub gave me their notes and first hand experience concerning this subject. In an effort not to dox themselves, they gave me permission to post on the matter....
Post-hoc explanation methods have often been criticised for abstracting away the decision-making process of deep neural networks. In this work, we would like to provide natural language descriptions for what different layers of a vision backbone have...
Current research in Computer Vision has shown that Convolutional Neural Networks (CNN) give state-of-the-art performance in many classification tasks and Computer Vision problems. The embedding of CNN, which is the internal representation produced by...
This thesis is divided into two parts:Part I: Analysis of Fruits, Vegetables, Cheese and Fish based on Image Processing using Computer Vision and Deep Learning: A Review. It consists of a comprehensive review of image processing, computer vision and...
This tool has been deprecated. Use Agentic Document Extraction instead. (⭐ 5262)
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Test-time prompt tuning (TPT) has emerged as a promising technique for adapting large vision-language models (VLMs) to unseen tasks without relying on labeled data. However, the lack of dispersion between textual features can hurt calibration perform...
Motorcycle accidents pose significant risks, particularly when riders and passengers do not wear helmets. This study evaluates the efficacy of an advanced vision-language foundation model, OWLv2, in detecting and classifying various helmet-wearing st...
⚠️ This repository is archived. Please use https://github.com/nbhr/pycalib . An Implementation of Takahashi, Nobuhara and Matsuyama "A New Mirror-based Camera Pose Estimation Using an Orthogonality Constraint" presented at CVPR 2012 (⭐ 33)
Unlearning methods for vision-language models (VLMs) have primarily adapted techniques from large language models (LLMs), relying on weight updates that demand extensive annotated forget sets. Moreover, these methods perform unlearning at a coarse gr...
After having many less than stellar experiences with YouTube on my Vision Pro, I said, “Fine, I'll do it myself!" I challenged myself to make the YouTube app that *I* would want to use. So I did! ...
Large Vision Language Models (VLMs) are now the de facto state-of-the-art for a number of tasks including visual question answering, recognising objects, and spatial referral. In this work, we propose the HOI-Ref task for egocentric images that aims...
The Apple Vision Pro is equipped with accurate eye-tracking capabilities, yet the privacy restrictions on the device prevent direct access to continuous user gaze data. This study introduces iTrace, a novel application that overcomes these limitation...
**Apple's visionOS 2 literally transforms any 2D photo into spatial 3D in 2-3 seconds using AI. Plus major upgrades for content creators. This changes everything.** # ? THE BIG DEAL: AI-Powered 2D...
Reducing traffic fatalities and serious injuries is a top priority of the US Department of Transportation. The computer vision (CV)-based crash anticipation in the near-crash phase is receiving growing attention. The ability to perceive fatal crash r...
Autonomous driving systems remain critically vulnerable to the long-tail of rare, out-of-distribution scenarios with semantic anomalies. While Vision Language Models (VLMs) offer promising reasoning capabilities, naive prompting approaches yield unre...
Vision Transformers achieve strong accuracy but incur high compute and memory cost. Structured pruning can reduce inference cost, but most methods rely on retraining or multi-stage optimization. These requirements limit post-training deployment. We p...
This is a disaster relief and rescue aid. It aims to reduce the issue of fragmented response by various organizations during the times of natural calamity. IMPACT HACKS'23 First Runner up (⭐ 6)
We introduce Shakti VLM, a family of vision-language models in the capacity of 1B and 4B parameters designed to address data efficiency challenges in multimodal learning. While recent VLMs achieve strong performance through extensive training data, S...