Trending Research
Adversarial Open Domain Adaption for Sketch-to-Photo Synthesis
In this paper, we explore the open-domain sketch-to-photo translation, which aims to synthesize a realistic photo from a freehand sketch with its class label, even if the sketches of that class are missing in the training data.
Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet
• lukemelas/do-you-even-need-attention
• 
These results indicate that aspects of vision transformers other than attention, such as the patch embedding, may be more responsible for their strong performance than previously thought.
Ranked #323 on
Image Classification
on ImageNet
LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference
We design a family of image classification architectures that optimize the trade-off between accuracy and efficiency in a high-speed regime.
Ranked #2 on
Image Classification
on ImageNet V2
ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision
Vision-and-Language Pretraining (VLP) has improved performance on various joint vision-and-language downstream tasks.
IMAGE-TO-TEXT RETRIEVAL TEXT-TO-IMAGE RETRIEVAL VISUAL QUESTION ANSWERING VISUAL REASONING
MLP-Mixer: An all-MLP Architecture for Vision
• lucidrains/mlp-mixer-pytorch
•
Convolutional Neural Networks (CNNs) are the go-to model for computer vision.
Ranked #9 on
Image Classification
on ImageNet
(using extra training data)
RealFormer: Transformer Likes Residual Attention
Transformer is the backbone of modern NLP models.
Ranked #2 on
Paraphrase Identification
on Quora Question Pairs
LANGUAGE MODELLING LINGUISTIC ACCEPTABILITY NATURAL LANGUAGE INFERENCE PARAPHRASE IDENTIFICATION SENTIMENT ANALYSIS
Emerging Properties in Self-Supervised Vision Transformers
In this paper, we question if self-supervised learning provides new properties to Vision Transformer (ViT) that stand out compared to convolutional networks (convnets).
Ranked #1 on
Copy Detection
on Copydays strong subset
COPY DETECTION SELF-SUPERVISED IMAGE CLASSIFICATION SELF-SUPERVISED LEARNING SEMANTIC SEGMENTATION VIDEO OBJECT DETECTION
RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition
• DingXiaoH/RepMLP
•
We propose RepMLP, a multi-layer-perceptron-style neural network building block for image recognition, which is composed of a series of fully-connected (FC) layers.
Ranked #246 on
Image Classification
on ImageNet
Beyond Self-attention: External Attention using Two Linear Layers for Visual Tasks
Attention mechanisms, especially self-attention, play an increasingly important role in deep feature representation in visual tasks.
IMAGE CLASSIFICATION IMAGE GENERATION POINT CLOUD CLASSIFICATION SEMANTIC SEGMENTATION
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
ICLR 2021
• google-research/vision_transformer
• 
While the Transformer architecture has become the de-facto standard for natural language processing tasks, its applications to computer vision remain limited.
Ranked #1 on
Fine-Grained Image Classification
on Oxford-IIIT Pets
(using extra training data)
DOCUMENT IMAGE CLASSIFICATION FINE-GRAINED IMAGE CLASSIFICATION