Dong Gong

• Full publication list: Google Scholar

2024

• CLAP4CLIP: Continual Learning with Probabilistic Finetuning for Vision-Language Models
  Saurav Jha, Dong Gong#, Lina Yao. (#corresponding author)
  Advances in Neural Information Processing Systems (NeurIPS), 2024. (#corresponding author)
  [Code]

• EGGen: Image Generation with Multi-entity Prior Learning through Entity Guidance
  Zhenhong Sun, Junyan Wang, Zhiyu Tan, Daoyi Dong, Hailan Ma, Li Hao, Dong Gong
  In ACM Multimedia (MM), 2024.
  

• SDGE: Stereo Guided Depth Estimation for 360°Camera Sets
  Jialei Xu, Wei Yin, Dong Gong, Junjun Jiang, Xianming Liu
  In International Conference on Intelligent Robots and Systems (IROS), 2024.
  

• Learning with Mixture of Prototypes for Out-of-Distribution Detection
  Haodong Lu, Dong Gong#, Shuo Wang, Jason Xue, Lina Yao, Kristen Moore.
  International Conference on Learning Representations (ICLR), 2024. (#corresponding author)
  [Code]

• Identifiable Latent Polynomial Causal Models Through the Lens of Change
  Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi.
  International Conference on Learning Representations (ICLR), 2024.
  

• Continual All-in-One Adverse Weather Removal With Knowledge Replay on a Unified Network Structure
  De Cheng, Yanling Ji, Dong Gong, Yan Li, Nannan Wang, Junwei Han, Dingwen Zhang.
  IEEE Transactions on Multimedia (TMM), 2024.
  [Code]

• Mining Your Own Secrets: Diffusion Classifier Scores for Continual Personalization of Text-to-Image Diffusion Models
  Saurav Jha, Shiqi Yang, Masato Ishii, Mengjie Zhao, Christian Simon, Muhammad Jehanzeb Mirza, Dong Gong, Lina Yao, Shusuke Takahashi, Yuki Mitsufuji
  In arXiv preprint, arXiv:2410.00700.
  

• Self-Expansion of Pre-trained Models with Mixture of Adapters for Continual Learning
  Huiyi Wang, Haodong Lu, Lina Yao, Dong Gong#. (#corresponding author)
  In arXiv preprint, arXiv:2403.18886.
  

• Premonition: Using Generative Models to Preempt Future Data Changes in Continual Learning
  Mark D. McDonnell, Dong Gong, Ehsan Abbasnejad, Anton van den Hengel.
  In arXiv preprint, arXiv:2403.19137.
  [Code]

• Revealing Multimodal Contrastive Representation Learning through Latent Partial Causal Models
  Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi.
  In arXiv preprint, arXiv:2402.06223, 2024.
  

2023

• NPCL: Neural Processes for Uncertainty-Aware Continual Learning
  Saurav Jha, Dong Gong#, He Zhao, Lina Yao.
  Advances in Neural Information Processing Systems (NeurIPS), 2023. (#corresponding author)
  [Code]

• RanPAC: Random Projections and Pre-trained Models for Continual Learning
  Mark D. McDonnell, Dong Gong, Amin Parveneh, Ehsan Abbasnejad, Anton van den Hengel.
  Advances in Neural Information Processing Systems (NeurIPS), 2023.
  [arXiv] [Code]

• Learning to Fuse Monocular and Multi-view Cues for Multi-Frame Depth Estimation in Dynamic Scenes
  Rui Li, Dong Gong#, Wei Yin#, Hao Chen, Yu Zhu, Kaixuan Wang, Xiaozhi Chen, Jinqiu Sun, Yanning Zhang# (#corresponding author)
  In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
  [arXiv] [Code] [Project]

• Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video Recognition
  Junyan Wang*, Zhenhong Sun*, Yichen Qian, Dong Gong, Xiuyu Sun, Ming Lin, Maurice Pagnucco, Yang Song. (* Equal contribution)
  International Conference on Learning Representations (ICLR), 2023.
  

• SharpFormer: Learning Local Feature Preserving Global Representations for Image Deblurring
  Qingsen Yan, Dong Gong, Pei Wang , Zhen Zhang , Yanning Zhang , Javen Qinfeng Shi.
  In IEEE Transactions on Image Processing (TIP), 2023.
  

2022

• Truncated Matrix Power Iteration for Differentiable DAG Learning
  Zhang, Zhen*, Ignavier Ng*, Dong Gong, Yuhang Liu, Ehsan M. Abbasnejad, Mingming Gong, Kun Zhang, and Javen Qinfeng Shi. (* Equal contribution)
  Advances in Neural Information Processing Systems (NeurIPS), 2022.
  

• Learning Bayesian Sparse Networks with Full Experience Replay for Continual Learning
  Qingsen Yan*, Dong Gong*, Yuhang Liu, Anton van den Hengel, Javen Qinfeng Shi (* Equal contribution)
  In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022. 
  [Project]

• A lightweight network for high dynamic range imaging
  Qingsen Yan, Song Zhang, Weiye Chen, Yuhang Liu, Zhen Zhang, Yanning Zhang, Javen Qinfeng Shi, Dong Gong
  In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2022.
  

• Dual-Attention-Guided Network for Ghost-Free High Dynamic Range Imaging
  Qingsen Yan*, Dong Gong*, Qinfeng Shi, Anton van den Hengel, Chunhua Shen, Ian Reid, Yanning Zhang (* Equal contribution)
  In International Journal of Computer Vision (IJCV), 2022. 
  

• Video Super-Resolution via Mixed Spatial-Temporal Convolution and Selective Fusion
  Wei Sun, Dong Gong, Javen Qinfeng Shi, Anton van den Hengel, Yanning Zhang
  Pattern Recognition (PR), 2022. 
  

2022 preprints

• The Neural Process Family: Survey, Applications and Perspectives
  Saurav Jha, Dong Gong, Xuesong Wang, Richard E. Turner, and Lina Yao
  arXiv:2209.00517, 2022.
  

• Identifying Latent Causal Content for Multi-Source Domain Adaptation
  Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Kun Zhang, and Javen Qinfeng Shi
  arXiv:2208.14161, 2022.
  

• Identifying Weight-Variant Latent Causal Models
  Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, and Javen Qinfeng Shi
  arXiv:2208.14153, 2022.
  

2021

• Memory-augmented Dynamic Neural Relational Inference
  Dong Gong, Zhen Zhang, Javen Shi, Anton van den Hengel
  In IEEE International Conference on Computer Vision (ICCV), 2021. (Accepted) 
  [Project]

• Learning to Zoom-in via Learning to Zoom-out: Real-world Super-resolution by Generating and Adapting Degradation
  Dong Gong*, Wei Sun*, Qinfeng Shi, Anton van den Hengel, Yanning Zhang (* Equal contribution)
  In IEEE Transactions on Image Processing (TIP).
  [arXiv]

• High Dynamic Range Imaging via Gradient-aware Context Aggregation Network
  Qingsen Yan*, Dong Gong*, Qinfeng Shi, Anton van den Hengel, Jinqiu Sun, Yu Zhu, Yanning Zhang (* Equal contribution)
  In Pattern Recognition (PR), 2021. (Accepted) 
  

• Boundarymix: Generating pseudo-training images for improving segmentation with scribble annotations
  Wanxuan Lu, Dong Gong, Kun Fu, Xian Sun, Wenhui Diao, and Lingqiao Liu
  In Pattern Recognition (PR), 2021.
  

• COVID-19 Chest CT Image Segmentation Network by Multi-Scale Fusion and Enhancement Operations.
  Qingsen Yan, Bo Wang, Dong Gong, Chuan Luo, Wei Zhao, Jianhu Shen, Jingyang Ai, Wei Zhao, Jianhu Shen, Jingyang Ai, Qinfeng Shi, Yanning Zhang, Shuo Jin, Liang Zhang, Zheng You
  In IEEE Transactions on Big Data 7, no. 1 (2021): 13-24.
  

2020

• Learning Deep Gradient Descent Optimization for Image Deconvolution
  Dong Gong, Zhen Zhang, Qinfeng Shi, Anton van den Hengel, Chunhua Shen, Yanning Zhang
  In IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2020.
  [Code]

• Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance Segmentation
  Tong He*, Dong Gong*, Zhi Tian, Chunhua Shen (* Equal contribution)
  In European Conference on Computer Vision (ECCV), 2020. 
  [arXiv] [Code]

• Deep Single Image Deraining via Modeling Haze-like Effect
  Yinglong Wang, Dong Gong, Jie Yang, Qinfeng Shi, Anton van den Hengel, Dehua Xie, Bing Zeng
  In IEEE Transactions on Multimedia (TMM), 2020. 
  

• Part-guided Attention Learning for Vehicle Instance Retrieval
  Xinyu Zhang, Rufeng Zhang, Jiewei Cao, Dong Gong, Mingyu You, and Chunhua Shen
  IEEE Transactions on Intelligent Transportation Systems (TITS), 2020. 
  [arXiv]

• Memorizing Comprehensively to Learn Adaptively: Unsupervised Cross-Domain Person Re-ID with Multi-level Memory
  Xinyu Zhang*, Dong Gong*, Jiewei Cao, Chunhua Shen (* Equal contribution)
  In arXiv preprint arXiv:2001.04123, 2020. 
  [arXiv]

• Semi-supervised Learning via Conditional Rotation Angle Estimation
  Hai-Ming Xu, Lingqiao Liu, Dong Gong
  In arXiv preprint arXiv:2001.02865, 2020. 
  [arXiv]

2019

• Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection
  Dong Gong, Lingqiao Liu, Vuong Le, Budhaditya Saha, Moussa Reda Mansour, Svetha Venkatesh, Anton van den Hengel
  In IEEE International Conference on Computer Vision (ICCV), 2019. 
  [arXiv] [Project] [Github]

• Regularizing Proxies with Multi-Adversarial Training for Unsupervised Domain-Adaptive Semantic Segmentation
  Tong Shen, Dong Gong, Wei Zhang, Chunhua Shen, Tao Mei
  In arXiv preprint arXiv:1907.12282, 2019. 
  [arXiv] [Github]

• Attention-guided Network for Ghost-free High Dynamic Range Imaging
  Qingsen Yan*, Dong Gong*, Qinfeng Shi, Anton van den Hengel, Chunhua Shen, Ian Reid, Yanning Zhang (* Equal contribution)
  In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
  [arXiv] [Github] [Project]

• RGBD Based Dimensional Decomposition Residual Network for 3D Semantic Scene Completion
  Jie Li, Yu Liu, Dong Gong, Qinfeng Shi, Xia Yuan, Chunxia Zhao, Ian Reid
  In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
  [arXiv] [Supp]

• Knowledge Translation and Adaptation for Efficient Semantic Segmentation
  Tong He, Chunhua Shen, Zhi Tian, Dong Gong, Changming Sun, Youliang Yan
  In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. 

• Variational Bayesian Dropout with a Hierarchical Prior
  Yuhang Liu, Wenyong Dong, Lei Zhang, Dong Gong, Qinfeng Shi
  In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
  [arXiv] [Project]

• Learning Sparse PCA with Stabilized ADMM Method on Stiefel Manifold
  Mingkui Tan, Zhibin Hu, Yuguang Yan, Jiezhang Cao, Dong Gong, Qingyao Wu
  In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019.

• Learning Distilled Graph for Large-scale Social Network Data Clustering
  Wenhe Liu, Dong Gong, Mingkui Tan, Qinfeng Shi, Yi Yang and Alexander G. Hauptmann
  In IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019.

• MPTV: Matching Pursuit Based Total Variation Minimization for Image Deconvolution
  Dong Gong, Mingkui Tan, Qinfeng Shi, Anton van den Hengel, Yanning Zhang
  In IEEE Transactions on Image Processing (TIP), Volume: 28, Issue: 4, 2019.
  [arXiv] [Supp] [Code] [Related work: MPGL]

• Two-Stream Convolutional Networks for Blind Image Quality Assessment
  Qingsen Yan*, Dong Gong*, Yanning Zhang (* Equal contribution)
  In IEEE Transactions on Image Processing (TIP), Volume: 28, Issue: 5, 2019.
  [Code]

• An Adaptive Markov Random Field for Structured Compressive Sensing
  Suwichaya Suwanwimolkul, Lei Zhang, Dong Gong, Zhen Zhang, Chao Chen, Damith C. Ranasinghe, Qinfeng Shi
  In IEEE Transactions on Image Processing (TIP), Volume: 28, Issue: 3, 2019.
  [arXiv]

2018

• Seeing Deeply and Bidirectionally: A Deep Learning Approach for Single Image Reflection Removal
  Jie Yang*, Dong Gong*, Lingqiao Liu, Qinfeng Shi (* Equal contribution)
  In European Conference on Computer Vision (ECCV), 2018.
  [Github]

• Deblurring Natural Image Using Super-Gaussian Fields
  Yuhang Liu, Wenyong Dong, Dong Gong, Lei Zhang, Qinfeng Shi
  In European Conference on Computer Vision (ECCV), 2018.
  [Code]

• Learning an Optimizer for Image Deconvolution
  Dong Gong, Zhen Zhang, Qinfeng Shi, Anton van den Hengel, Chunhua Shen, Yanning Zhang
  In arXiv preprint arXiv:1804.03368, 2018.
  [arXiv][Github]

2017

• Self-paced Kernel Estimation for Robust Blind Image Deblurring
  Dong Gong, Mingkui Tan, Yanning Zhang, Anton van den Hengel, Qinfeng Shi
  In IEEE International Conference on Computer Vision (ICCV), 2017.
  [Data&Results] [Code]

• From Motion Blur to Motion Flow: a Deep Learning Solution for Removing Heterogeneous Motion Blur
  Dong Gong, Jie Yang, Lingqiao Liu, Yanning Zhang, Ian Reid, Chunhua Shen, Anton van den Hengel, Qinfeng Shi
  In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017.
  [Code] [Data generation code] [Project]

• MPGL: An Efficient Matching Pursuit Method for Generalized LASSO
  Dong Gong, Mingkui Tan, Yanning Zhang, Anton van den Hengel, Qinfeng Shi
  In Thirty-First AAAI Conference on Artificial Intelligence (AAAI), 2017. Oral
  [Paper] [Supp] [Github] [Code] [Project]

2016

• Blind Image Deconvolution by Automatic Gradient Activation
  Dong Gong, Mingkui Tan, Yanning Zhang, Anton van den Hengel, Qinfeng Shi
  In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016.
  [Paper] [Project]

Before 2016

• Joint Motion Deblurring with Blurred Noisy Image Pair
  Haisen Li, Yanning Zhang, Jinqiu Sun, Dong Gong
  In 22nd International Conference on Pattern Recognition (ICPR), 2014.

• Neighbor Combination for Atmospheric Turbulence Image Reconstruction
  Dong Gong, Yanning Zhang, Shaobo Dang, Jinqiu Sun
  In IEEE International Conference on Image Processing (ICIP), 2013.