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Name: 涂云斌
Type: User
Company: University of Chinese Academy of Sciences
Location: Beijing, China
Name: 涂云斌
Type: User
Company: University of Chinese Academy of Sciences
Location: Beijing, China
Show, Attend, and Tell | a PyTorch Tutorial to Image Captioning
[ACL 2024] This is the Pytorch code for our paper "Context-aware Difference Distilling for Multi-change Captioning".
[ECCV 2024] This is the Pytorch code for our paper "Distractors-Immune Representation Learning with Cross-modal Contrastive Regularization for Change Captioning".
[Pattern Rcognition 2021] This is the Theano code for our paper "Enhancing the Alignment between Target Words and Corresponding Frames for Video Captioning".
The is the Pytorch version of our paper "Enhancing-the-Alignment-between-Target-Words-and-Corresponding-Frames-for-Video-Captioning" published in "Pattern Rcognition".
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[IEEE TIP 2022] This is Pytorch code for our paper "I2Transformer: Intra- and Inter-relation Embedding Transformer for TV Show Captioning".
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现,也是作为一个算法工程师必会的理论基础知识。
[IEEE TMM 2023] This is the Pytorch code for our paper "Neighborhood Contrastive Transformer for Change Captioning".
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
[EMNLP 2021] This is the Pytorch code for our paper "R^3Net:Relation-embedded Representation Reconstruction Network for Change Captioning".
[ICCV 2023] This is the Pytorch code for our paper "Self-Supervised Cross-View Representation Reconstruction for Change Captioning".
[IEEE TPAMI 2024] This is the Pytorch code for our paper "SMART: Syntax-calibrated Multi-Aspect Relation Transformer for Change Captioning".
[ACL 2021] This is the Pytorch code for our paper "Semantic Relation-aware Difference Representation Learning for Change Captioning".
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[IEEE TIP 2023] This is the Pytorch code for our paper "Viewpoint-Adaptive Representation Disentanglement Network for Change Captioning".
[ACM MM 2017 & IEEE TMM 2020] This is the Theano code for the paper "Video Description with Spatial Temporal Attention"
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