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Visual Question Answering

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

5

평가표

30

보존된 평가 기록

334

코드

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

https://github.com/bronyayang/HallE_Switch

공식 코드

HallE-Control: Controlling Object Hallucination in Large Multimodal Models

https://github.com/bronyayang/halle_control

공식 코드

HallE-Control: Controlling Object Hallucination in Large Multimodal Models

https://github.com/bscho333/ReVisiT

공식 코드

Revisit What You See: Disclose Language Prior in Vision Tokens for Efficient Guided Decoding of LVLMs

https://github.com/btzyd/qava

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QAVA: Query-Agnostic Visual Attack to Large Vision-Language Models

https://github.com/bytedance/MTVQA

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MTVQA: Benchmarking Multilingual Text-Centric Visual Question Answering

https://github.com/bytedance/lvlm_interpretation

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Where do Large Vision-Language Models Look at when Answering Questions?

https://github.com/byungkwanlee/meteor

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Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models

https://github.com/byungkwanlee/phantom

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Phantom of Latent for Large Language and Vision Models

https://github.com/byungkwanlee/trol

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TroL: Traversal of Layers for Large Language and Vision Models

https://github.com/c-patsch/okcv

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Outside Knowledge Conversational Video (OKCV) Dataset -- Dialoguing over Videos

https://github.com/cambridgeltl/topviewrs

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TopViewRS: Vision-Language Models as Top-View Spatial Reasoners

https://github.com/cambridgeltl/visual-spatial-reasoning

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Visual Spatial Reasoning

https://github.com/camma-public/ssg-qa

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Advancing Surgical VQA with Scene Graph Knowledge

https://github.com/camma-public/ssg-vqa

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Advancing Surgical VQA with Scene Graph Knowledge

https://github.com/castorini/unirag

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UniRAG: Universal Retrieval Augmentation for Large Vision Language Models

https://github.com/cciiplab/dpt

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Declaration-based Prompt Tuning for Visual Question Answering

https://github.com/ccqym/osmlocator

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OsmLocator: locating overlapping scatter marks with a non-training generative perspective

https://github.com/ccychongyanchen/vizwizvqagroundingcrowdsourcing

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Grounding Answers for Visual Questions Asked by Visually Impaired People

https://github.com/ccychongyanchen/vqatherapycrowdsourcing

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VQA Therapy: Exploring Answer Differences by Visually Grounding Answers

https://github.com/cdancette/detect-shortcuts

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Beyond Question-Based Biases: Assessing Multimodal Shortcut Learning in Visual Question Answering

https://github.com/cdancette/rubi.bootstrap.pytorch

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RUBi: Reducing Unimodal Biases in Visual Question Answering

https://github.com/chantalmp/rad-restruct

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Rad-ReStruct: A Novel VQA Benchmark and Method for Structured Radiology Reporting

https://github.com/chaoyi-wu/radfm

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Towards Generalist Foundation Model for Radiology by Leveraging Web-scale 2D&3D Medical Data

https://github.com/chengyuehuang511/frames-vqa

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FRAMES-VQA: Benchmarking Fine-Tuning Robustness across Multi-Modal Shifts in Visual Question Answering

https://github.com/chenzcv7/motor

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Towards Medical Artificial General Intelligence via Knowledge-Enhanced Multimodal Pretraining

https://github.com/child-play-neurips/child-play

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Show, Don't Tell: Evaluating Large Language Models Beyond Textual Understanding with ChildPlay

https://github.com/chojw/genb

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Generative Bias for Robust Visual Question Answering

https://github.com/chrisc36/autobias

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Learning to Model and Ignore Dataset Bias with Mixed Capacity Ensembles

https://github.com/chrisc36/debias

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Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases

https://github.com/christopher-beckham/clevr-mrt

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Visual Question Answering From Another Perspective: CLEVR Mental Rotation Tests

https://github.com/chunmeifeng/vqa4cir

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VQA4CIR: Boosting Composed Image Retrieval with Visual Question Answering

https://github.com/circleradon/tokenpacker

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TokenPacker: Efficient Visual Projector for Multimodal LLM

https://github.com/clause-bielefeld/illusionofcompetence-vqa-explanations

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The Illusion of Competence: Evaluating the Effect of Explanations on Users' Mental Models of Visual Question Answering Systems

https://github.com/clear-nus/gpt-pddl

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Translating Natural Language to Planning Goals with Large-Language Models

https://github.com/clip-vil/CLIP-ViL

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How Much Can CLIP Benefit Vision-and-Language Tasks?

https://github.com/cliport/cliport

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CLIPort: What and Where Pathways for Robotic Manipulation

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