research
∙
07/03/2023
ACDMSR: Accelerated Conditional Diffusion Models for Single Image Super-Resolution
Diffusion models have gained significant popularity in the field of imag...
share
research
∙
06/01/2023
A Transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics
During the diagnostic process, clinicians leverage multimodal informatio...
research
∙
04/17/2023
Everyone Can Be Picasso? A Computational Framework into the Myth of Human versus AI Painting
The recent advances of AI technology, particularly in AI-Generated Conte...
research
∙
08/14/2022
Semi-Supervised Video Inpainting with Cycle Consistency Constraints
Deep learning-based video inpainting has yielded promising results and g...
research
∙
08/11/2022
On the Pros and Cons of Momentum Encoder in Self-Supervised Visual Representation Learning
Exponential Moving Average (EMA or momentum) is widely used in modern se...
research
∙
07/30/2022
A Survey on Masked Autoencoder for Self-supervised Learning in Vision and Beyond
Masked autoencoders are scalable vision learners, as the title of MAE <c...
research
∙
07/22/2022
Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial Robustness
Adversarial training (AT) for robust representation learning and self-su...
research
∙
07/05/2022
Understanding and Improving Group Normalization
Various normalization layers have been proposed to help the training of ...
research
∙
03/30/2022
Investigating Top-k White-Box and Transferable Black-box Attack
Existing works have identified the limitation of top-1 attack success ra...
research
∙
03/30/2022
Dual Temperature Helps Contrastive Learning Without Many Negative Samples: Towards Understanding and Simplifying MoCo
Contrastive learning (CL) is widely known to require many negative sampl...
research
∙
03/30/2022
How Does SimSiam Avoid Collapse Without Negative Samples? A Unified Understanding with Self-supervised Contrastive Learning
To avoid collapse in self-supervised learning (SSL), a contrastive loss ...
research
∙
02/11/2022
Noise Augmentation Is All You Need For FGSM Fast Adversarial Training: Catastrophic Overfitting And Robust Overfitting Require Different Augmentation
Adversarial training (AT) and its variants are the most effective approa...
research
∙
03/01/2021
Query Rewriting via Cycle-Consistent Translation for E-Commerce Search
Nowadays e-commerce search has become an integral part of many people's ...
research
∙
06/03/2020
Towards Personalized and Semantic Retrieval: An End-to-End Solution for E-commerce Search via Embedding Learning
Nowadays e-commerce search has become an integral part of many people's ...
research
∙
06/03/2020
Towards Personalized and Semantic Retrieval: An End-to-EndSolution for E-commerce Search via Embedding Learning
Nowadays e-commerce search has become an integral part of many people's ...
research
∙
09/13/2017
A Computational Model of Afterimages based on Simultaneous and Successive Contrasts
Negative afterimage appears in our vision when we shift our gaze from an...
research
∙
10/06/2014
Bayesian regression and Bitcoin
In this paper, we discuss the method of Bayesian regression and its effi...
research
∙
02/10/2014
