Papers with Code 아카이브
Visual Reasoning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 평가표
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- 보존된 평가 기록
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Ability to understand actions and reasoning associated with any visual images
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/shijx12/shijx12.github.io
https://github.com/shin-ee-chen/bla
https://github.com/shivammehta25/clip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/shkarupa-alex/tfclip
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/shunk031/simple-aesthetics-predictor
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/si0wang/vicrit
SoTA with Less: MCTS-Guided Sample Selection for Data-Efficient Visual Reasoning Self-Improvement
https://github.com/sincerass/mvlpt
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/sithu31296/simple-object-tracking
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/skunkworksai/bakllava
https://github.com/social-ai-studio/matk
VisualBERT: A Simple and Performant Baseline for Vision and Language
https://github.com/sshh12/multi_token
https://github.com/sunsmarterjie/chatterbox
https://github.com/tabtoyou/kollava
https://github.com/taited/clip-score
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/tajamul21/fate
https://github.com/tanhuajie/reason-rft
https://github.com/teticio/llama-squad
https://github.com/thaolmk54/LOGNet-VQA
https://github.com/thudm/visualglm-6b
https://github.com/tohinz/pytorch-mac-network
https://github.com/towhee-io/towhee
Learning Transferable Visual Models From Natural Language Supervision
https://github.com/towhee-io/towhee/tree/main/towhee/models/coformer
Collaborative Transformers for Grounded Situation Recognition
https://github.com/uclanlp/visualbert
VisualBERT: A Simple and Performant Baseline for Vision and Language
https://github.com/ucsc-vlaa/vlaa-thinking
SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models
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
https://github.com/visioncortex/vtracer
Visually Descriptive Language Model for Vector Graphics Reasoning
https://github.com/vista-h/gpt-4v_social_media
CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs
https://github.com/vladsandulescu/hatefulmemes
https://github.com/vmurahari3/visdial-bert
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
https://github.com/weixin-liang/metashift
GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering
https://github.com/wglab/gestaltmml
ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision
https://github.com/wglab/gestaltmml-gestaltgpt
ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision
https://github.com/woodfrog/vse_infty
https://github.com/xiaomin418/cfsum
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.