Papers
Deep Parametric 3D Filters for Joint Video Denoising and Illumination Enhancement in Video Super Resolution
Xiaogang Xu, Ruixing Wang, Chi-Wing Fu et al.
Deep Spiking Neural Networks with High Representation Similarity Model Visual Pathways of Macaque and Mouse
Liwei Huang, Zhengyu Ma, Liutao Yu et al.
Deep Visual Forced Alignment: Learning to Align Transcription with Talking Face Video
Minsu Kim, Chae Won Kim, Yong Man Ro
Defending against Backdoor Attacks in Natural Language Generation
Xiaofei Sun, Xiaoya Li, Yuxian Meng et al.
Defending Backdoor Attacks on Vision Transformer via Patch Processing
Khoa D. Doan, Yingjie Lao, Peng Yang et al.
Defending Black-Box Skeleton-Based Human Activity Classifiers
He Wang, Yunfeng Diao, Zichang Tan et al.
Defending from Physically-Realizable Adversarial Attacks through Internal Over-Activation Analysis
Giulio Rossolini, Federico Nesti, Fabio Brau et al.
DeFL: Defending against Model Poisoning Attacks in Federated Learning via Critical Learning Periods Awareness
Gang Yan, Hao Wang, Xu Yuan et al.
Delving Deep into Pixel Alignment Feature for Accurate Multi-View Human Mesh Recovery
Kai Jia, Hongwen Zhang, Liang An et al.
Delving into the Adversarial Robustness of Federated Learning
Jie Zhang, Bo Li, Chen Chen et al.
Demo Alleviate: Demonstrating Artificial Intelligence Enabled Virtual Assistance for Telehealth: The Mental Health Case
Kaushik Roy, Vedant Khandelwal, Raxit Goswami et al.
DeMT: Deformable Mixer Transformer for Multi-Task Learning of Dense Prediction
Yangyang Xu, Yibo Yang, Lefei Zhang
Demystifying Randomly Initialized Networks for Evaluating Generative Models
Junghyuk Lee, Jun-Hyuk Kim, Jong-Seok Lee
Demystify the Gravity Well in the Optimization Landscape (Student Abstract)
Jason Xiaotian Dou, Runxue Bao, Susan Song et al.
DENet: Disentangled Embedding Network for Visible Watermark Removal
Ruizhou Sun, Yukun Su, Qingyao Wu
DE-net: Dynamic Text-Guided Image Editing Adversarial Networks
Ming Tao, Bing-Kun Bao, Hao Tang et al.
Denoising after Entropy-Based Debiasing a Robust Training Method for Dataset Bias with Noisy Labels
Sumyeong Ahn, Se-Young Yun
Denoising Multi-Similarity Formulation: A Self-Paced Curriculum-Driven Approach for Robust Metric Learning
Chenkang Zhang, Lei Luo, Bin Gu
Denoising Pre-training for Machine Translation Quality Estimation with Curriculum Learning
Xiang Geng, Yu Zhang, Jiahuan Li et al.
Design Amortization for Bayesian Optimal Experimental Design
Noble Kennamer, Steven Walton, Alexander Ihler
DesNet: Decomposed Scale-Consistent Network for Unsupervised Depth Completion
Zhiqiang Yan, Kun Wang, Xiang Li et al.
DetAIL: A Tool to Automatically Detect and Analyze Drift in Language
Nishtha Madaan, Adithya Manjunatha, Hrithik Nambiar et al.
Detecting and Grounding Important Characters in Visual Stories
Danyang Liu, Frank Keller
Detecting Anomalous Networks of Opioid Prescribers and Dispensers in Prescription Drug Data
Katie Rosman, Daniel B. Neill
Detecting Exclusive Language during Pair Programming
Solomon Ubani, Rodney Nielsen, Helen Li