Dong Gong
34 papers · 2016–2026 · 8 venues · across top CS/AI venues
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Research topics
Machine Learning
(20)
Deep Learning
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Learning Types Β· Machine Learning
(14)
Artificial Intelligence
(13)
Computer Vision
(11)
Core AI
(11)
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(8)
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(3)
Keywords
continual learning
(7)
catastrophic forgetting
(4)
semantic segmentation
(3)
representation learning
(3)
knowledge distillation
(3)
diffusion model
(3)
fully convolutional network
(2)
causal representation learning
(2)
class prototype
(2)
variational inference
(2)
causal discovery
(2)
domain adaptation
(2)
vision-language model
(2)
directed acyclic graph
(2)
distribution shift
(2)
contrastive learning
(2)
zero-shot learning
(2)
pre-trained model
(2)
uncertainty estimation
(2)
anomaly detection
(1)
Papers
Hierarchical Point-Patch Fusion with Adaptive Patch Codebook for 3D Shape Anomaly Detection
CVPR 2026
Identifying Weight-Variant Latent Causal Models
JMLR 2026
Let Your Image Move with Your Motion! -- Implicit Multi-Object Multi-Motion Transfer
CVPR 2026
On Token's Dilemma: Dynamic MoE with Drift-Aware Token Assignment for Continual Learning of Large Vision Language Models
CVPR 2026
Socrates or Smartypants: Testing Logic Reasoning Capabilities of Large Language Models with Logic Programming-Based Test Oracles
AAAI 2026
Analytic DAG Constraints for Differentiable DAG Learning
ICLR 2025
Coreset Selection via Reducible Loss in Continual Learning
ICLR 2025
D^3CTTA: Domain-Dependent Decorrelation for Continual Test-Time Adaption of 3D LiDAR Segmentation
CVPR 2025
DyMO: Training-Free Diffusion Model Alignment with Dynamic Multi-Objective Scheduling
CVPR 2025
Is Less More? Exploring Token Condensation as Training-free Test-time Adaptation
ICCV 2025
Mining your own secrets: Diffusion Classifier Scores for Continual Personalization of Text-to-Image Diffusion Models
ICLR 2025
Seeing the Unseen: Composing Outliers for Compositional Zero-Shot Learning
IJCAI 2025
Self-Expansion of Pre-trained Models with Mixture of Adapters for Continual Learning
CVPR 2025
CLAP4CLIP: Continual Learning with Probabilistic Finetuning for Vision-Language Models
NeurIPS 2024
Identifiable Latent Polynomial Causal Models through the Lens of Change
ICLR 2024
Learning with Mixture of Prototypes for Out-of-Distribution Detection
ICLR 2024
Learning To Fuse Monocular and Multi-View Cues for Multi-Frame Depth Estimation in Dynamic Scenes
CVPR 2023
Maximizing Spatio-Temporal Entropy of Deep 3D CNNs for Efficient Video Recognition
ICLR 2023
NPCL: Neural Processes for Uncertainty-Aware Continual Learning
NeurIPS 2023
RanPAC: Random Projections and Pre-trained Models for Continual Learning
NeurIPS 2023
Learning Bayesian Sparse Networks With Full Experience Replay for Continual Learning
CVPR 2022
Truncated Matrix Power Iteration for Differentiable DAG Learning
NeurIPS 2022
Memory-Augmented Dynamic Neural Relational Inference
ICCV 2021
Learning and Memorizing Representative Prototypes for 3D Point Cloud Semantic and Instance Segmentation
ECCV 2020
Attention-Guided Network for Ghost-Free High Dynamic Range Imaging
CVPR 2019
Knowledge Adaptation for Efficient Semantic Segmentation
CVPR 2019
Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection
ICCV 2019
RGBD Based Dimensional Decomposition Residual Network for 3D Semantic Scene Completion
CVPR 2019
Variational Bayesian Dropout With a Hierarchical Prior
CVPR 2019
Deblurring Natural Image Using Super-Gaussian Fields
ECCV 2018
Seeing Deeply and Bidirectionally: A Deep Learning Approach for Single Image Reflection Removal
ECCV 2018
From Motion Blur to Motion Flow: A Deep Learning Solution for Removing Heterogeneous Motion Blur
CVPR 2017
Self-Paced Kernel Estimation for Robust Blind Image Deblurring
ICCV 2017
Blind Image Deconvolution by Automatic Gradient Activation
CVPR 2016