Papers with Code 아카이브

Visual Question Answering

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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하위 태스크

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평가표

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보존된 평가 기록

334

코드

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

https://github.com/sts-vlcc/sts-vlcc

Zero-Shot Video Question Answering via Frozen Bidirectional Language Models

https://github.com/sunsmarterjie/chatterbox

Visual Instruction Tuning

https://github.com/sy-sunmoon/Clever-Commenter-Let-s-Try-More-Apps

Dynamic Memory Networks for Visual and Textual Question Answering

https://github.com/syscv/sam-hq

SpatialRGPT: Grounded Spatial Reasoning in Vision Language Models

https://github.com/tabtoyou/kollava

Visual Instruction Tuning

https://github.com/tanjimin/grad-cam-pytorch-light

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

https://github.com/tarolangner/mri-biometry

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

https://github.com/tashchowdhury/FloodNet-Supervised_v1.0

FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding

https://github.com/tbmoon/basic_vqa

VQA: Visual Question Answering

https://github.com/teddykoker/image-forensics

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

https://github.com/tejas-gokhale/vqa_mutant

MUTANT: A Training Paradigm for Out-of-Distribution Generalization in Visual Question Answering

https://github.com/thaolmk54/LOGNet-VQA

Dynamic Language Binding in Relational Visual Reasoning

https://github.com/therne/dmn-tensorflow

Dynamic Memory Networks for Visual and Textual Question Answering

https://github.com/thilinicooray/Bottom-up-vqa

Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering

https://github.com/thtang/CheXNet-with-localization

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

https://github.com/thudm/visualglm-6b

BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

https://github.com/thunlp/pevl

MDETR -- Modulated Detection for End-to-End Multi-Modal Understanding

https://github.com/tianaidong/2021splu-robonlp-vispa

GuessWhat?! Visual object discovery through multi-modal dialogue

https://github.com/tianhai123/tf-faster-rcnn

Spatial Memory for Context Reasoning in Object Detection

https://github.com/tidedra/vl-rlhf

RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human Feedback

https://github.com/tigerofmurder/tf-faster-rcnn

Spatial Memory for Context Reasoning in Object Detection

https://github.com/tinyllava/tinyllava_factory

TinyLLaVA: A Framework of Small-scale Large Multimodal Models

https://github.com/tongjingqi/code2logic

SWIFT:A Scalable lightWeight Infrastructure for Fine-Tuning

https://github.com/trisha-c-a/Visual-Question-Answering-with-Keras

FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding

https://github.com/tsurumeso/chainer-grad-cam

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

https://github.com/ttok0s7u2n5/ML2_proj

A simple neural network module for relational reasoning

https://github.com/turningpoint-ai/visualthinker-r1-zero

SAT: Dynamic Spatial Aptitude Training for Multimodal Language Models

https://github.com/uakarsh/TiLT-Implementation

Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer

https://github.com/uakarsh/latr

LaTr: Layout-Aware Transformer for Scene-Text VQA

https://github.com/uds-lsv/pypremise

Label-Descriptive Patterns and Their Application to Characterizing Classification Errors

https://github.com/ukyh/switch_disc_caption

Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering

https://github.com/umass-foundation-model/genome

GENOME: GenerativE Neuro-symbOlic visual reasoning by growing and reusing ModulEs

https://github.com/unispac/visual-adversarial-examples-jailbreak-large-language-models

Flamingo: a Visual Language Model for Few-Shot Learning

https://github.com/valdecy/pybibx

Gemini: A Family of Highly Capable Multimodal Models

https://github.com/vargpt-family/vargpt-v1.1

VARGPT: Unified Understanding and Generation in a Visual Autoregressive Multimodal Large Language Model

https://github.com/vbbphc/GradCAM.jl

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

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