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08/26/2023
MST-compression: Compressing and Accelerating Binary Neural Networks with Minimum Spanning Tree
Binary neural networks (BNNs) have been widely adopted to reduce the com...
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06/25/2023
Faster Segment Anything: Towards Lightweight SAM for Mobile Applications
Segment anything model (SAM) is a prompt-guided vision foundation model ...
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05/10/2023
Generative AI meets 3D: A Survey on Text-to-3D in AIGC Era
Generative AI (AIGC, a.k.a. AI generated content) has made remarkable pr...
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05/01/2023
Attack-SAM: Towards Evaluating Adversarial Robustness of Segment Anything Model
Segment Anything Model (SAM) has attracted significant attention recentl...
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04/29/2023
Segment Anything Model (SAM) Meets Glass: Mirror and Transparent Objects Cannot Be Easily Detected
Meta AI Research has recently released SAM (Segment Anything Model) whic...
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04/04/2023
A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Material
Diffusion models have become a new SOTA generative modeling method in va...
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04/04/2023
One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Era
OpenAI has recently released GPT-4 (a.k.a. ChatGPT plus), which is demon...
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03/26/2023
Analyzing Effects of Mixed Sample Data Augmentation on Model Interpretability
Data augmentation strategies are actively used when training deep neural...
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03/23/2023
A Survey on Audio Diffusion Models: Text To Speech Synthesis and Enhancement in Generative AI
Generative AI has demonstrated impressive performance in various fields,...
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03/21/2023
A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?
As ChatGPT goes viral, generative AI (AIGC, a.k.a AI-generated content) ...
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10/17/2022
ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization
Recent advances on large-scale pre-training have shown great potentials ...
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11/09/2021
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps
Deep neural networks are susceptible to adversarially crafted, small and...
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09/02/2021
Adversarial Robustness for Unsupervised Domain Adaptation
Extensive Unsupervised Domain Adaptation (UDA) studies have shown great ...
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09/15/2020
AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results
This paper reviews the AIM 2020 challenge on efficient single image supe...
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08/29/2020
Ultra Lightweight Image Super-Resolution with Multi-Attention Layers
Lightweight image super-resolution (SR) networks have the utmost signifi...
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06/19/2020
Towards an Adversarially Robust Normalization Approach
Batch Normalization (BatchNorm) is effective for improving the performan...
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06/02/2020
SaliencyMix: A Saliency Guided Data Augmentation Strategy for Better Regularization
Advanced data augmentation strategies have widely been studied to improv...
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07/16/2019
An Inter-Layer Weight Prediction and Quantization for Deep Neural Networks based on a Smoothly Varying Weight Hypothesis
Network compression for deep neural networks has become an important par...
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07/11/2019
Hybrid Residual Attention Network for Single Image Super Resolution
The extraction and proper utilization of convolution neural network (CNN...
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06/25/2019
New pointwise convolution in Deep Neural Networks through Extremely Fast and Non Parametric Transforms
Some conventional transforms such as Discrete Walsh-Hadamard Transform (...
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05/10/2017
Efficient and Scalable View Generation from a Single Image using Fully Convolutional Networks
Single-image-based view generation (SIVG) is important for producing 3D ...
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05/09/2017