Papers with Code 아카이브

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/Yushi-Hu/tifa

공식 코드

TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering

https://github.com/Yuuxii/Black-box-QA-Ensemling

공식 코드

Black-box Model Ensembling for Textual and Visual Question Answering via Information Fusion

https://github.com/ZephyrZhuQi/ssbaseline

공식 코드

Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps

https://github.com/ZhengxiangShi/StepGame

공식 코드

StepGame: A New Benchmark for Robust Multi-Hop Spatial Reasoning in Texts

https://github.com/ZuyiZhou/Awesome-Interpretable-Cross-modal-Reasoning

공식 코드

A Survey on Interpretable Cross-modal Reasoning

https://github.com/abril4416/Mod-Zero-VQA

공식 코드

Modularized Zero-shot VQA with Pre-trained Models

https://github.com/abril4416/kgen_vqa

공식 코드

Knowledge Generation for Zero-shot Knowledge-based VQA

https://github.com/abskjha/Barlow-constrained-VQA

공식 코드

Barlow constrained optimization for Visual Question Answering

https://github.com/abzb1/f-clip

공식 코드

Vision-Encoders (Already) Know What They See: Mitigating Object Hallucination via Simple Fine-Grained CLIPScore

https://github.com/activevisionlab/awesome-llm-3d

공식 코드

When LLMs step into the 3D World: A Survey and Meta-Analysis of 3D Tasks via Multi-modal Large Language Models

https://github.com/adacheng/egothink

공식 코드

EgoThink: Evaluating First-Person Perspective Thinking Capability of Vision-Language Models

https://github.com/adapter-hub/xgqa

공식 코드

xGQA: Cross-Lingual Visual Question Answering

https://github.com/adishourya/medm

공식 코드

Adapting Lightweight Vision Language Models for Radiological Visual Question Answering

https://github.com/aditya10/vlc-bert

공식 코드

VLC-BERT: Visual Question Answering with Contextualized Commonsense Knowledge

https://github.com/adityakane2001/continual_vqa

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Continual VQA for Disaster Response Systems

https://github.com/adlnlp/MultimodalLLM

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Multimodal Large Language Models and Tunings: Vision, Language, Sensors, Audio, and Beyond

https://github.com/adlnlp/attention_vl

공식 코드

Understanding Attention for Vision-and-Language Tasks

https://github.com/ag2ai/simpledoc

공식 코드

SimpleDoc: Multi-Modal Document Understanding with Dual-Cue Page Retrieval and Iterative Refinement

https://github.com/ahmad-shirazi/AnnotMLLM

공식 코드

DLaVA: Document Language and Vision Assistant for Answer Localization with Enhanced Interpretability and Trustworthiness

https://github.com/ahmedmagdiosman/clevr-xai

공식 코드

Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI

https://github.com/ahmedmagdiosman/simply-clevr-dataset

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Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI

https://github.com/ai4ce/CityWalker

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CityWalker: Learning Embodied Urban Navigation from Web-Scale Videos

https://github.com/ai4ce/Contrastive-SPARE3D

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Self-supervised Spatial Reasoning on Multi-View Line Drawings

https://github.com/ai4ce/SPARE3D

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SPARE3D: A Dataset for SPAtial REasoning on Three-View Line Drawings

https://github.com/aidaslab/second

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SECOND: Mitigating Perceptual Hallucination in Vision-Language Models via Selective and Contrastive Decoding

https://github.com/aifeg/benchgpt

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BenchLMM: Benchmarking Cross-style Visual Capability of Large Multimodal Models

https://github.com/aifeg/benchlmm

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BenchLMM: Benchmarking Cross-style Visual Capability of Large Multimodal Models

https://github.com/ailab-cvc/vl-gpt

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VL-GPT: A Generative Pre-trained Transformer for Vision and Language Understanding and Generation

https://github.com/aimagelab/reflectiva

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Augmenting Multimodal LLMs with Self-Reflective Tokens for Knowledge-based Visual Question Answering

https://github.com/aimbrain/vqa-project

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Learning Conditioned Graph Structures for Interpretable Visual Question Answering

https://github.com/aioz-ai/ECCVW20_MILQT

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Multiple interaction learning with question-type prior knowledge for constraining answer search space in visual question answering

https://github.com/aioz-ai/ICCV19_VQA-CTI

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Compact Trilinear Interaction for Visual Question Answering

https://github.com/aioz-ai/MICCAI19-MedVQA

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Overcoming Data Limitation in Medical Visual Question Answering

https://github.com/aioz-ai/MICCAI21_MMQ

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Multiple Meta-model Quantifying for Medical Visual Question Answering

https://github.com/aioz-ai/cfr_vqa

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Coarse-to-Fine Reasoning for Visual Question Answering

https://github.com/aioz-ai/crf_vqa

공식 코드

Coarse-to-Fine Reasoning for Visual Question Answering

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