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09/21/2023
TinyCLIP: CLIP Distillation via Affinity Mimicking and Weight Inheritance
In this paper, we propose a novel cross-modal distillation method, calle...
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05/25/2023
Image is First-order Norm+Linear Autoregressive
This paper reveals that every image can be understood as a first-order n...
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02/27/2023
Layer Grafted Pre-training: Bridging Contrastive Learning And Masked Image Modeling For Label-Efficient Representations
Recently, both Contrastive Learning (CL) and Mask Image Modeling (MIM) d...
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11/23/2022
Self-Supervised Learning based on Heat Equation
This paper presents a new perspective of self-supervised learning based ...
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08/20/2022
Visual Analysis of Neural Architecture Spaces for Summarizing Design Principles
Recent advances in artificial intelligence largely benefit from better n...
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07/21/2022
TinyViT: Fast Pretraining Distillation for Small Vision Transformers
Vision transformer (ViT) recently has drawn great attention in computer ...
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07/07/2022
Should All Proposals be Treated Equally in Object Detection?
The complexity-precision trade-off of an object detector is a critical p...
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06/07/2022
Detection Hub: Unifying Object Detection Datasets via Query Adaptation on Language Embedding
Leveraging large-scale data can introduce performance gains on many comp...
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05/10/2022
Reduce Information Loss in Transformers for Pluralistic Image Inpainting
Transformers have achieved great success in pluralistic image inpainting...
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04/20/2022
Residual Mixture of Experts
Mixture of Experts (MoE) is able to scale up vision transformers effecti...
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04/14/2022
MiniViT: Compressing Vision Transformers with Weight Multiplexing
Vision Transformer (ViT) models have recently drawn much attention in co...
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11/22/2021
Florence: A New Foundation Model for Computer Vision
Automated visual understanding of our diverse and open world demands com...
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08/12/2021
Mobile-Former: Bridging MobileNet and Transformer
We present Mobile-Former, a parallel design of MobileNet and Transformer...
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08/12/2021
MicroNet: Improving Image Recognition with Extremely Low FLOPs
This paper aims at addressing the problem of substantial performance deg...
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06/15/2021
Dynamic Head: Unifying Object Detection Heads with Attentions
The complex nature of combining localization and classification in objec...
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03/29/2021
CvT: Introducing Convolutions to Vision Transformers
We present in this paper a new architecture, named Convolutional vision ...
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03/15/2021
Revisiting Dynamic Convolution via Matrix Decomposition
Recent research in dynamic convolution shows substantial performance boo...
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02/21/2021
Weak NAS Predictors Are All You Need
Neural Architecture Search (NAS) finds the best network architecture by ...
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11/24/2020
MicroNet: Towards Image Recognition with Extremely Low FLOPs
In this paper, we present MicroNet, which is an efficient convolutional ...
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08/21/2020
A Survey of Visual Analytics Techniques for Machine Learning
Visual analytics for machine learning has recently evolved as one of the...
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07/28/2020
Diagnosing Concept Drift with Visual Analytics
Concept drift is a phenomenon in which the distribution of a data stream...
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03/27/2020
DA-NAS: Data Adapted Pruning for Efficient Neural Architecture Search
Efficient search is a core issue in Neural Architecture Search (NAS). It...
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03/22/2020
Dynamic ReLU
Rectified linear units (ReLU) are commonly used in deep neural networks....
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12/07/2019
Dynamic Convolution: Attention over Convolution Kernels
Light-weight convolutional neural networks (CNNs) suffer performance deg...
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10/09/2018
Analyzing the Noise Robustness of Deep Neural Networks
Deep neural networks (DNNs) are vulnerable to maliciously generated adve...
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02/04/2017
Towards Better Analysis of Machine Learning Models: A Visual Analytics Perspective
Interactive model analysis, the process of understanding, diagnosing, an...
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04/24/2016
Towards Better Analysis of Deep Convolutional Neural Networks
Deep convolutional neural networks (CNNs) have achieved breakthrough per...
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12/13/2015