Machine Learning with a Honk
Massimiliano ViolaWeekly insights into machine learning research, focusing on computer vision and generative models.
| Platform |  | Pricing | Only free issues | Publishes | Weekly |
|---|---|---|---|---|---|
| Issues | 60 | Founded | a year ago | Last Issue | 7 days ago |
| Active | |||||
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60. Sapiens and Sapiens2
Introduction
Image foundation models learn powerful features from massive datasets with the goal of maximizing performance on a wide range of tasks. But when it comes to human-centric vision applications, such as fine-grained body part s...
59. From AM-RADIO to C-RADIOv4
Introduction
Over the last five years, industry research in computer vision has produced a wide variety of foundation models. Powerful, general, and trained on large datasets, they have historically dominated certain tasks but consistent...
58. Utonia
Introduction
In a previous post (#46), we covered Sonata [2] and Concerto [3], two strong 3D point cloud encoders trained with self-supervised learning.
Sonata is essentially DINO for 3D: a student sees local and masked crops of a point...
57. TIPS and TIPSv2
Introduction
Throughout our deep dives into major pretraining paradigms for vision encoders, we have repeatedly identified a tradeoff between dense feature quality (e.g., DINO) and alignment with text (e.g., CLIP) for downstream applicat...
56. ViTPose and ViTPose++
Pose estimation visualized. From dzone.com
Introduction
Pose estimation is the task of localizing anatomical keypoints on an image. For humans, this means predicting the locations of true joints such as shoulders, elbows, wrists, hips,...
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Authors
The writers behind this newsletter.
Perception & Safety at Bedrock Robotics. Previously at Cerrion (YC S22), Stanford, and ETH Zurich.
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