Trending Research
A ConvNet for the 2020s
The "Roaring 20s" of visual recognition began with the introduction of Vision Transformers (ViTs), which quickly superseded ConvNets as the state-of-the-art image classification model.
Ranked #1 on
Domain Generalization
on ImageNet-Sketch
(using extra training data)
Masked Autoencoders Are Scalable Vision Learners
Our MAE approach is simple: we mask random patches of the input image and reconstruct the missing pixels.
Ranked #1 on
Image Classification
on iNaturalist 2019
Extracting Triangular 3D Models, Materials, and Lighting From Images
We present an efficient method for joint optimization of topology, materials and lighting from multi-view image observations.
Deep Learning Interviews: Hundreds of fully solved job interview questions from a wide range of key topics in AI
BoltzmannEntropy/interviews.ai
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The second edition of Deep Learning Interviews is home to hundreds of fully-solved problems, from a wide range of key topics in AI.
Detecting Twenty-thousand Classes using Image-level Supervision
For the first time, we train a detector with all the twenty-one-thousand classes of the ImageNet dataset and show that it generalizes to new datasets without fine-tuning.
A 1D CNN for high accuracy classification and transfer learning in motor imagery EEG-based brain-computer interface
Kubasinska/MI-EEG-1D-CNN
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Journal of Neural Engineering 2022
In addition, we present a transfer learning method used to extract critical features from the EEG group dataset and then to customize the model to the single individual by training its late layers with only 12-min individual-related data.
MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer
xmu-xiaoma666/External-Attention-pytorch
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In this paper, we ask the following question: is it possible to combine the strengths of CNNs and ViTs to build a light-weight and low latency network for mobile vision tasks?
Ranked #379 on
Image Classification
on ImageNet
CoAtNet: Marrying Convolution and Attention for All Data Sizes
xmu-xiaoma666/External-Attention-pytorch
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NeurIPS 2021
Transformers have attracted increasing interests in computer vision, but they still fall behind state-of-the-art convolutional networks.
Ranked #1 on
Image Classification
on ImageNet
(using extra training data)
Layered Neural Atlases for Consistent Video Editing
ykasten/layered-neural-atlases
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We present a method that decomposes, or "unwraps", an input video into a set of layered 2D atlases, each providing a unified representation of the appearance of an object (or background) over the video.
Feature Selection Methods for Uplift Modeling
uber/causalml
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To address this problem, we introduce a set of feature selection methods designed specifically for uplift modeling, including both filter methods and embedded methods.
