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    <title>yuyu4Tech</title>
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    <lastBuildDate>2026-04-13 13:51:19 -0400</lastBuildDate>
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      <title>【論文紹介】DINOv3: Self-supervised Learning for Vision at Unprecedented Scale</title>
      <description>DINOv3 is Meta AI's latest vision foundation model that pushes self-supervised learning to an unprecedented scale.

This talk introduces the key ideas behind DINOv3, including:

Large-scale data curation (17B images)
Self-supervised pre-training with DINO and iBOT objectives
Gram Anchoring for dense feature preservation
High-resolution adaptation up to 4K+ inference
Efficient multi-student distillation

We will explore how these innovations enable DINOv3 to achieve state-of-the-art performance across a broad range of computer vision tasks while improving scalability, robustness, and deployment efficiency.</description>
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      <content:encoded>DINOv3 is Meta AI's latest vision foundation model that pushes self-supervised learning to an unprecedented scale.

This talk introduces the key ideas behind DINOv3, including:

Large-scale data curation (17B images)
Self-supervised pre-training with DINO and iBOT objectives
Gram Anchoring for dense feature preservation
High-resolution adaptation up to 4K+ inference
Efficient multi-student distillation

We will explore how these innovations enable DINOv3 to achieve state-of-the-art performance across a broad range of computer vision tasks while improving scalability, robustness, and deployment efficiency.</content:encoded>
      <pubDate>Tue, 02 Jun 2026 00:00:00 -0400</pubDate>
      <link>https://speakerdeck.com/yuyu4tech/lun-wen-shao-jie-dinov3-self-supervised-learning-for-vision-at-unprecedented-scale</link>
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      <title>【論文紹介】DINOv2: Seeing Without Supervision</title>
      <description>A deep dive into Meta AI's self-supervised vision foundation model — exploring how DINOv2 learns robust visual features from 142M curated images without any labels, and why it rivals weakly-supervised methods across classification, segmentation, depth estimation, and beyond.
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      <content:encoded>A deep dive into Meta AI's self-supervised vision foundation model — exploring how DINOv2 learns robust visual features from 142M curated images without any labels, and why it rivals weakly-supervised methods across classification, segmentation, depth estimation, and beyond.
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      <pubDate>Mon, 13 Apr 2026 00:00:00 -0400</pubDate>
      <link>https://speakerdeck.com/yuyu4tech/lun-wen-shao-jie-dinov2-seeing-without-supervision</link>
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