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This project is a computer vision benchmark and image classification dataset used to measure and compare the accuracy of machine learning models. It provides a standardized collection of labeled fashion product images and training data formatted to be compatible with the MNIST dataset structure. The dataset consists of fixed-dimension grayscale images and label-based category mappings, stored in a binary format. It includes pre-split training and testing sets and a static distribution to ensure consistent cross-model benchmarking. The repository supports image classification benchmarking and
Qwen2-VL is a multimodal large language model and vision language model designed to process and reason across text, images, and video content. It functions as a visual reasoning engine and a visual agent framework, capable of interpreting visual data to perform object detection, document parsing, and spatial reasoning. The model is distinguished by its ability to act as a video understanding model, processing hour-long videos with second-level indexing and event recall. It further differentiates itself through a visual agent capability that interacts with software interfaces and robotic hardw
Code for "Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks", Gupta et al, CVPR 2018
This repository contains the code for training and evaluating the various models presented in the paper IQA: Visual Question Answering in Interactive Environments. It also provides an interface for reading the questions and generating new questions if desired.
The main features of danielgordon10/thor-iqa-cvpr-2018 are: Computer Vision Research, Embodied Question Answering, Visual Interactions.
Projects with overlapping indexed features include: facebookresearch/embodiedqa — Code for the paper. qwenlm/qwen2-vl — Qwen2-VL is a multimodal large language model and vision language model designed to process and reason across text,… zalandoresearch/fashion-mnist — This project is a computer vision benchmark and image classification dataset used to measure and compare the accuracy… agrimgupta92/sgan — Code for "Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks", Gupta et al, CVPR 2018. akanazawa/cmr — Angjoo Kanazawa \ , Shubham Tulsiani \ , Alexei A. Efros, Jitendra Malik. aimerykong/recurrent-pixel-embedding-for-instance-grouping — CVPR2018 - pixel embedding & grouping for structured prediction, e.g., instance segmentation.
