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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/lavi-lab/visual-table

공식 코드

Beyond Embeddings: The Promise of Visual Table in Visual Reasoning

https://github.com/laytextllm/laytextllm

공식 코드

A Bounding Box is Worth One Token: Interleaving Layout and Text in a Large Language Model for Document Understanding

https://github.com/leitro/selfattnscoring-mpdocvqa

공식 코드

Multi-Page Document Visual Question Answering using Self-Attention Scoring Mechanism

https://github.com/letitiabanana/pnp-ovss

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Emergent Open-Vocabulary Semantic Segmentation from Off-the-shelf Vision-Language Models

https://github.com/li-qingyun/mllm-mmrotate

공식 코드

A Simple Aerial Detection Baseline of Multimodal Language Models

https://github.com/libeineu/mmt-vqa

공식 코드

Incorporating Probing Signals into Multimodal Machine Translation via Visual Question-Answering Pairs

https://github.com/lijiannuist/efficient-multimodal-llms-survey

공식 코드

Efficient Multimodal Large Language Models: A Survey

https://github.com/lik1996/crvqa2024

공식 코드

Convincing Rationales for Visual Question Answering Reasoning

https://github.com/like413/vista

공식 코드

Show Me What and Where has Changed? Question Answering and Grounding for Remote Sensing Change Detection

https://github.com/lil-lab/knotgym

공식 코드

Knot So Simple: A Minimalistic Environment for Spatial Reasoning

https://github.com/lil-lab/touchdown

공식 코드

Touchdown: Natural Language Navigation and Spatial Reasoning in Visual Street Environments

https://github.com/lilidamowang/iiu

공식 코드

IIU: Independent Inference Units for Knowledge-based Visual Question Answering

https://github.com/limiaoyu/dietcoke

공식 코드

Diversify, Rationalize, and Combine: Ensembling Multiple QA Strategies for Zero-shot Knowledge-based VQA

https://github.com/lin-tianwei/teamlora

공식 코드

TeamLoRA: Boosting Low-Rank Adaptation with Expert Collaboration and Competition

https://github.com/linjieli222/VQA_ReGAT

공식 코드

Relation-Aware Graph Attention Network for Visual Question Answering

https://github.com/linjiemu/mmxu

공식 코드

MMXU: A Multi-Modal and Multi-X-ray Understanding Dataset for Disease Progression

https://github.com/lins-lab/dynmoe

공식 코드

Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models

https://github.com/linweizhedragon/retrieval-augmented-visual-question-answering

공식 코드

Retrieval Augmented Visual Question Answering with Outside Knowledge

https://github.com/linzhiqiu/t2i_metrics

공식 코드

Evaluating Text-to-Visual Generation with Image-to-Text Generation

https://github.com/linzhiqiu/t2v_metrics

공식 코드

Evaluating Text-to-Visual Generation with Image-to-Text Generation

https://github.com/linzhiqiu/visual_gpt_score

공식 코드

Revisiting the Role of Language Priors in Vision-Language Models

https://github.com/liqing-ustc/NGS

공식 코드

Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning

https://github.com/liuhc0428/med-pmc

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Med-PMC: Medical Personalized Multi-modal Consultation with a Proactive Ask-First-Observe-Next Paradigm

https://github.com/liuting20/dara

공식 코드

DARA: Domain- and Relation-aware Adapters Make Parameter-efficient Tuning for Visual Grounding

https://github.com/liuziyu77/mmdu

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MMDU: A Multi-Turn Multi-Image Dialog Understanding Benchmark and Instruction-Tuning Dataset for LVLMs

https://github.com/liweim/TextLayoutLLM

공식 코드

Large Language Models Understand Layout

https://github.com/lizw14/calico

공식 코드

Calibrating Concepts and Operations: Towards Symbolic Reasoning on Real Images

https://github.com/lizw14/super-clevr

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Super-CLEVR: A Virtual Benchmark to Diagnose Domain Robustness in Visual Reasoning

https://github.com/lkaesberg/sparc

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SPaRC: A Spatial Pathfinding Reasoning Challenge

https://github.com/llamatouch/vlm-reasoning-traces

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Does Chain-of-Thought Reasoning Help Mobile GUI Agent? An Empirical Study

https://github.com/lmb-freiburg/ovqa

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Open-ended VQA benchmarking of Vision-Language models by exploiting Classification datasets and their semantic hierarchy

https://github.com/longbai1006/cat-vil

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CAT-ViL: Co-Attention Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery

https://github.com/longbai1006/surgical-vqlaplus

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Surgical-VQLA++: Adversarial Contrastive Learning for Calibrated Robust Visual Question-Localized Answering in Robotic Surgery

https://github.com/ltu-machine-learning/idocvqa

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Instruction Makes a Difference

https://github.com/lunaproject22/causalchaos

공식 코드

CausalChaos! Dataset for Comprehensive Causal Action Question Answering Over Longer Causal Chains Grounded in Dynamic Visual Scenes

https://github.com/luodian/otter

공식 코드

Otter: A Multi-Modal Model with In-Context Instruction Tuning

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