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Visual Question Answering

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전체 기법전체 데이터셋

하위 태스크

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평가표

30

보존된 평가 기록

334

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/2toinf/ivm

공식 코드

Instruction-Guided Visual Masking

https://github.com/AIF4S/MediConfusion

공식 코드

MediConfusion: Can you trust your AI radiologist? Probing the reliability of multimodal medical foundation models

https://github.com/AIGeeksGroup/3DCoCa

공식 코드

3D CoCa: Contrastive Learners are 3D Captioners

https://github.com/AIM-SKKU/QA-TIGER

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Question-Aware Gaussian Experts for Audio-Visual Question Answering

https://github.com/ASMIftekhar/VSGNet

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VSGNet: Spatial Attention Network for Detecting Human Object Interactions Using Graph Convolutions

https://github.com/Abhiram4572/mi_bart

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Answer Mining from a Pool of Images: Towards Retrieval-Based Visual Question Answering

https://github.com/Abhishek0697/Detection-of-Hate-Speech-in-Multimodal-Memes

공식 코드

Detecting Hate Speech in Multi-modal Memes

https://github.com/AikyamLab/hallucinogen

공식 코드

HALLUCINOGEN: A Benchmark for Evaluating Object Hallucination in Large Visual-Language Models

https://github.com/Aishwarya-NR/LRTA_Perturbed_Dataset

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LRTA: A Transparent Neural-Symbolic Reasoning Framework with Modular Supervision for Visual Question Answering

https://github.com/Akutagawa1998/LazyBench

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Difficult Task Yes but Simple Task No: Unveiling the Laziness in Multimodal LLMs

https://github.com/AlexJJJChen/Climate-Zoo

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Vision-Language Models Meet Meteorology: Developing Models for Extreme Weather Events Detection with Heatmaps

https://github.com/AlexKuhnle/ShapeWorld

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ShapeWorld - A new test methodology for multimodal language understanding

https://github.com/BierOne/VQA-AttReg

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Answer Questions with Right Image Regions: A Visual Attention Regularization Approach

https://github.com/Bravo5542/TJSTG

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Target-Aware Spatio-Temporal Reasoning via Answering Questions in Dynamics Audio-Visual Scenarios

https://github.com/ByungKwanLee/CoLLaVO

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CoLLaVO: Crayon Large Language and Vision mOdel

https://github.com/ByungKwanLee/MoAI

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MoAI: Mixture of All Intelligence for Large Language and Vision Models

https://github.com/CMFiltenborg/lingually_constrained_tracking

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Siamese Tracking with Lingual Object Constraints

https://github.com/CSU-JPG/MVPBench

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Seeing is Not Reasoning: MVPBench for Graph-based Evaluation of Multi-path Visual Physical CoT

https://github.com/CYandYue/Dentist

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A Unified Hallucination Mitigation Framework for Large Vision-Language Models

https://github.com/Cadene/block.bootstrap.pytorch

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BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection

https://github.com/Cadene/murel.bootstrap.pytorch

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MUREL: Multimodal Relational Reasoning for Visual Question Answering

https://github.com/Cadene/vqa.pytorch

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MUTAN: Multimodal Tucker Fusion for Visual Question Answering

https://github.com/Chat-3D/Chat-3D

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Chat-3D: Data-efficiently Tuning Large Language Model for Universal Dialogue of 3D Scenes

https://github.com/ChenRocks/UNITER

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UNITER: UNiversal Image-TExt Representation Learning

https://github.com/China-UK-ZSL/ZS-F-VQA

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Zero-shot Visual Question Answering using Knowledge Graph

https://github.com/Cold-Winter/vqs

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VQS: Linking Segmentations to Questions and Answers for Supervised Attention in VQA and Question-Focused Semantic Segmentation

https://github.com/CraftJarvis/ROCKET-1

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ROCKET-1: Mastering Open-World Interaction with Visual-Temporal Context Prompting

https://github.com/CrossmodalGroup/SSL-VQA

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Overcoming Language Priors with Self-supervised Learning for Visual Question Answering

https://github.com/Cyanogenoid/perm-optim

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Learning Representations of Sets through Optimized Permutations

https://github.com/Cyanogenoid/vqa-counting

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Learning to Count Objects in Natural Images for Visual Question Answering

https://github.com/DS3Lab/WordScape

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WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data

https://github.com/Deanplayerljx/tab-vcr

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TAB-VCR: Tags and Attributes based Visual Commonsense Reasoning Baselines

https://github.com/DelTA-Lab-IITK/CCM-WACV

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Robust Explanations for Visual Question Answering

https://github.com/Depth2World/VLADBench

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Fine-Grained Evaluation of Large Vision-Language Models in Autonomous Driving

https://github.com/DoubtedSteam/MM-GCoT

공식 코드

Grounded Chain-of-Thought for Multimodal Large Language Models

https://github.com/DreadPiratePsyopus/Fine_Grained_Clf

공식 코드

Fine-grained Image Classification and Retrieval by Combining Visual and Locally Pooled Textual Features

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.