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Causal Intervention for Weakly-Supervised Semantic Segmentation[oral]
34th Conference on Neural Information Processing Systems, NeurIPS 2020, Vancouver, Canada.
[arxiv][github]
Interventional Few-Shot Learning
34th Conference on Neural Information Processing Systems, NeurIPS 2020, Vancouver, Canada.
[arxiv][github]
Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect
34th Conference on Neural Information Processing Systems, NeurIPS 2020, Vancouver, Canada.
[arxiv][github]
Hierarchical Scene Graph Encoder-Decoder for Image Paragraph Captioning
ACM Multimedia 2020.
[preprint coming soon]
Counterfactual VQA: A Cause-Effect Look at Language Bias
[arxiv preprint]
Feature Pyramid Transformer
European Conference on Computer Vision. ECCV 2020
[arxiv preprint][github]
Self-Adaptive Neural Module Transformer for Visual Question Answering
IEEE Transactions on Multimedia. TMM 2020
[IEEExplore]
Iterative Context-Aware Graph Inference for Visual Dialog[oral]
IEEE International Conference on Computer Vision and Pattern Recognition. CVPR 2020. Seattle, USA. June 2020
[arxiv preprint][github]
Unbiased Scene Graph Generation from Biased Training[oral]
IEEE International Conference on Computer Vision and Pattern Recognition. CVPR 2020. Seattle, USA. June 2020
[arxiv preprint][github]
Deconfounded Image Captioning: A Causal Retrospect
[arxiv preprint]
Visual Commonsense R-CNN
IEEE International Conference on Computer Vision and Pattern Recognition. CVPR 2020. Seattle, USA. June 2020
Hanwang Laptops For Senior Citizens
[arxiv preprint][github]
Hanwang Laptops Amazon
Two Causal Principles for Improving Visual Dialog
IEEE International Conference on Computer Vision and Pattern Recognition. CVPR 2020. Seattle, USA. June 2020
[arxiv preprint][github]
Learning to Segment the Tail
IEEE International Conference on Computer Vision and Pattern Recognition. CVPR 2020. Seattle, USA. June 2020
[arxiv preprint][github]
Counterfactual Samples Synthesizing for Robust Visual Question Answering
IEEE International Conference on Computer Vision and Pattern Recognition. CVPR 2020. Seattle, USA. June 2020
[arxiv preprint][github]
More Grounded Image Captioning by Distilling Image-Text Matching Model
IEEE International Conference on Computer Vision and Pattern Recognition. CVPR 2020. Seattle, USA. June 2020
[arxiv preprint][github]
Learning Filter Pruning Criteria for Deep Convolutional Neural Networks Acceleration
IEEE International Conference on Computer Vision and Pattern Recognition. CVPR 2020. Seattle, USA. June 2020
[release soon]
Multi-Level Policy and Reward-Based Deep Reinforcement Learning Framework for Image Captioning
IEEE Transactions on Multimedia. TMM 2020
[Link]
General Partial Label Learning via Dual Bipartite Graph Autoencoder
The AAAI Conference on Artificial Intelligence. AAAI 2020
[arxiv preprint]
MReaL Lab
Welcome to Machine Reasoning and Learning (MReaL) Lab. MReaL Lab mainly focuses on the fusion of deep learning and reasoning for computer vision, such as visual captioning, visual question answering, scene graph generation, visual dialog, visual grounding, panoptic segmentation, meta-structure learning and so on.
About me
I am leading MReal Lab at Nanyang Technological University (NTU). I am a Nanyang Assistant Professor. Before this, I was doing a post-doc job at DVMM, whose boss is Prof. Shih-Fu Chang. Before this job, I worked with Prof. Tat-Seng Chua, who is also my Ph.D supervisor (2009 - 2014) and Assoc. Prof. Shuicheng Yan (2013 - 2014). And, before this, I was an undergraduate student of Zhejiang University (2005 - 2009). In particular, I was a member of Chu Kochen Honors College.
Research
Welcome to Machine Reasoning and Learning (MReaL) Lab. MReaL Lab mainly focuses on the fusion of deep learning and reasoning for computer vision, such as visual captioning, visual question answering, scene graph generation, visual dialog, visual grounding, panoptic segmentation, meta-structure learning and so on.