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Nov 4, 2022 · In this paper, we focus on learning lightweight ViT models and formulate both the quantization and distillation strategies into the multi-exit framework.
Nov 10, 2022 · In this paper, we focus on learning lightweight ViT models and formulate both the quantization and distillation strategies into the multi-exit ...
Training a Lightweight ViT Network for Image Retrieval. https://doi.org/10.1007/978-3-031-20868-3_18 ·. Journal: Lecture Notes in Computer Science PRICAI ...
Recently, Vision Transformer (ViT) networks have achieved promising advancements on many computer vision tasks. However, a ViT network has a large number of ...
Apr 18, 2024 · Masked image modeling (MIM) pre-training for large-scale vision transformers (ViTs) in computer vision has enabled promising downstream performance.
In this work, we introduce a new approach to obtain a global image rep- resentation from a vision transfomer. We perform extensive experiments on several ...
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Duration: 3:54
Posted: Jan 29, 2024
Posted: Jan 29, 2024
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Despite their impressive performance on various tasks, vision transformers (ViTs) are heavy for mobile vision applications. Recent works have proposed ...
Feb 14, 2022 · Abstract. Transformers have shown outstanding results for natural language understanding and, more re- cently, for image classification.
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How do you train a neural network for image recognition?
What is ViT for image recognition?
Vision Transformers (ViT) brought recent breakthroughs in Computer Vision achieving state-of-the-art accuracy with better efficiency.
Missing: Retrieval. | Show results with:Retrieval.