https://github.com/vchudinov/dynamic_memory_networks_with_keras
Dynamic Memory Networks for Visual and Textual Question Answering
Papers with Code 아카이브
Visual Question Answering
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/vietlinhtspt/NewFasterRCNN
https://github.com/vikrantmane7781/detectroon2
Multi-modal Factorized Bilinear Pooling with Co-Attention Learning for Visual Question Answering
https://github.com/vincentschen/limited-label-scene-graphs
https://github.com/virajprabhu/premise-emnlp17
The Promise of Premise: Harnessing Question Premises in Visual Question Answering
https://github.com/vladsandulescu/hatefulmemes
https://github.com/vmurahari3/visdial-diversity
Learning Cooperative Visual Dialog Agents with Deep Reinforcement Learning
https://github.com/vohoaiviet/FloorNet
FloorNet: A Unified Framework for Floorplan Reconstruction from 3D Scans
https://github.com/voxmenthe/OmniNet_1
OmniNet: A unified architecture for multi-modal multi-task learning
https://github.com/wangzpeng/tf-faster-rcnn
https://github.com/wawaku/grad-cam-keras
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/wayveai/driving-with-llms
https://github.com/wennieWN/endernewton_tf-faster-rcnn
https://github.com/windweller/PragmaticVQA
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/wsanchezdupont1/Grad-CAM
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/x-plug/mplug
mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections
https://github.com/xaviercanche/Grad-CAM
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/xiaobai714/image_caption
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/xiaoduoailab/xmodellm
Xmodel-VLM: A Simple Baseline for Multimodal Vision Language Model
https://github.com/xiaomin418/cfsum
https://github.com/xikai97/med-mim
https://github.com/xinding-sys/StreamMind
Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding
https://github.com/xinpingwang/tf-faster-rcnn
https://github.com/xinwei666/mmgenerativeir
Weakly-Supervised Visual-Retriever-Reader for Knowledge-based Question Answering
https://github.com/xn1997/pytorch-grad-cam
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/xuewyang/Fashion_Captioning
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/yaleCat/Grad-CAM-pytorch
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
https://github.com/yanchunyu71/relational-networks-paddle
https://github.com/yangdsh/VQA-BUTD-demo
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
https://github.com/yangyucheng000/University/tree/main/model-2/blip_2
https://github.com/yangyucheng000/University/tree/main/model-2/cogvlm
CogVLM2: Visual Language Models for Image and Video Understanding
https://github.com/yangyucheng000/University/tree/main/model-2/internlm
https://github.com/yangyucheng000/University/tree/main/model-3/qwen2_vl
Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
https://github.com/yangyucheng000/papercode-2/tree/main/LRSL-main
https://github.com/yanxinyan1/yxy
https://github.com/yifanh1/gqa_pytorch
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.