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06/01/2023
Can Large Pre-trained Models Help Vision Models on Perception Tasks?
The recent upsurge in pre-trained large models (e.g. GPT-4) has swept ac...
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05/30/2023
GPT4GEO: How a Language Model Sees the World's Geography
Large language models (LLMs) have shown remarkable capabilities across a...
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04/03/2023
DreamAvatar: Text-and-Shape Guided 3D Human Avatar Generation via Diffusion Models
We present DreamAvatar, a text-and-shape guided framework for generating...
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07/21/2022
Novel Class Discovery without Forgetting
Humans possess an innate ability to identify and differentiate instances...
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06/01/2022
Vision GNN: An Image is Worth Graph of Nodes
Network architecture plays a key role in the deep learning-based compute...
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11/24/2021
An Image Patch is a Wave: Phase-Aware Vision MLP
Different from traditional convolutional neural network (CNN) and vision...
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10/12/2021
Open-Set Recognition: A Good Closed-Set Classifier is All You Need
The ability to identify whether or not a test sample belongs to one of t...
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06/27/2021
Post-Training Quantization for Vision Transformer
Recently, transformer has achieved remarkable performance on a variety o...
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02/27/2021
Transformer in Transformer
Transformer is a type of self-attention-based neural networks originally...
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01/21/2021
GhostSR: Learning Ghost Features for Efficient Image Super-Resolution
Modern single image super-resolution (SISR) system based on convolutiona...
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06/17/2020
LSD-C: Linearly Separable Deep Clusters
We present LSD-C, a novel method to identify clusters in an unlabeled da...
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06/16/2020
Dual-Resolution Correspondence Networks
We tackle the problem of establishing dense pixel-wise correspondences b...
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11/27/2019
