#Vqa
Showing 23 of 23 repositories tagged #vqa, ranked by stars
A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
Open-source evaluation toolkit of large multi-modality models (LMMs), support 220+ LMMs, 80+ benchmarks
InternGPT (iGPT) is an open source demo platform where you can easily showcase your AI models. Now it supports DragGAN, ChatGPT, ImageBind, multimodal chat like GPT-4, SAM, interactive image editing, etc. Try it at igpt.opengvlab.com (支持DragGAN、ChatGPT、ImageBind、SAM的在线Demo系统)
[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
Visual Question Answering in Pytorch
Chatbot Arena meets multi-modality! Multi-Modality Arena allows you to benchmark vision-language models side-by-side while providing images as inputs. Supports MiniGPT-4, LLaMA-Adapter V2, LLaVA, BLIP-2, and many more!
PyTorch implementation of "Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning"
Multimodal Question Answering in the Medical Domain: A summary of Existing Datasets and Systems
[ICLR'24] Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning
Awesome LLM Papers and repos on very comprehensive topics.
Tensorflow Implementation of Deeper LSTM+ normalized CNN for Visual Question Answering
Code release for NeurIPS 2023 paper SlotDiffusion: Object-centric Learning with Diffusion Models
This repo is for Amazon ML Challenge 2024. The challenge was to develop a Machine Learning model to extract product details directly from the product images.
A Deep Learning based No-reference Quality Assessment Model for UGC Videos
This project is out of date, I don't remember the details inside...
CloudCV Visual Question Answering Demo
Neuro-Symbolic Visual Question Answering on Sort-of-CLEVR using PyTorch
Multimodal Instruction Tuning for Llama 3
Gamified Adversarial Prompting (GAP): Crowdsourcing AI-weakness-targeting data through gamification. Boost model performance with community-driven, strategic data collection
실제 한국어 문서 데이터셋을 기반으로 만든 VLM 벤치마크 데이터셋
visual question answering prompting recipes for large vision-language models
[CVPR 2026 Highlight] ReAG: Reasoning-Augmented Generation for Knowledge-based Visual Question Answering
[CVPR 2025] Code for "Notes-guided MLLM Reasoning: Enhancing MLLM with Knowledge and Visual Notes for Visual Question Answering".