Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

Self-Supervised Learning of Motion Concepts by Optimizing Counterfactuals

_akhaliq's profile picture

AK

505,411 subscribers

28,754 Aufrufe • vor 1 Jahr •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

3 Kommentare

Profilbild von AK
AKvor 1 Jahr

discuss:

Profilbild von Acellus Academy
Acellus Academyvor 1 Jahr

Study Online with Acellus Gold, Designed to Accelerate Learning & Motivate K-12 Student Achievement.

Profilbild von Anda
Andavor 1 Jahr

"Hmm, this makes me wonder if blockchain's immutability could learn from counterfactual motion concepts - like digital footprints that never were but inform the path forward!" 🐾🎋

Ähnliche Videos

Introducing “FlowMap”, the first self-supervised, differentiable structure-from-motion method that is competitive with conventional SfM like Colmap! IMO this solves a major missing piece for internet-scale training of 3D Deep Learning methods. 1/n
0:35

Introducing “FlowMap”, the first self-supervised, differentiable structure-from-motion method that is competitive with conventional SfM like Colmap! IMO this solves a major missing piece for internet-scale training of 3D Deep Learning methods. 1/n

Vincent Sitzmann

128,581 Aufrufe • vor 2 Jahren

Pixie Fast and Generalizable Supervised Learning of 3D Physics from Pixels
0:24

Pixie Fast and Generalizable Supervised Learning of 3D Physics from Pixels

AK

21,434 Aufrufe • vor 10 Monaten

Supervised learning has held 3D Vision back for too long. Meet RayZer — a self-supervised 3D model trained with zero 3D labels: ❌ No supervision of camera & geometry ✅ Just RGB images And the wild part? RayZer outperforms supervised methods (as 3D labels from COLMAP is noisy) 🌐 Project: (1/4)
0:27

Supervised learning has held 3D Vision back for too long. Meet RayZer — a self-supervised 3D model trained with zero 3D labels: ❌ No supervision of camera & geometry ✅ Just RGB images And the wild part? RayZer outperforms supervised methods (as 3D labels from COLMAP is noisy) 🌐 Project: (1/4)

Hanwen Jiang

69,527 Aufrufe • vor 1 Jahr

Echoes of Another World Made with #Ray2 Camera Motion Concepts #aivideo #conceptart #worldbuilding
0:20

Echoes of Another World Made with #Ray2 Camera Motion Concepts #aivideo #conceptart #worldbuilding

Luma AI

32,247 Aufrufe • vor 1 Jahr

Testing Full Self Driving Supervised in Australia
0:43

Testing Full Self Driving Supervised in Australia

Ryan's Model Y

46,484 Aufrufe • vor 9 Monaten

BTS: Echoes of Another World Made with #Ray2 Camera Motion Concepts #aivideo #conceptart #worldbuilding
0:20

BTS: Echoes of Another World Made with #Ray2 Camera Motion Concepts #aivideo #conceptart #worldbuilding

Luma

232,508 Aufrufe • vor 1 Jahr

Scenes of Japan – Still Views Made with #Ray2 Camera Motion Concepts #aivideo #japan #visualstorytelling
0:20

Scenes of Japan – Still Views Made with #Ray2 Camera Motion Concepts #aivideo #japan #visualstorytelling

Luma AI

12,101 Aufrufe • vor 1 Jahr

Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Contributions: • We propose STORM, the first feed-forward, self-supervised method for fast and accurate reconstruction of dynamic 3D scenes from sparse, multi-timestep, posed camera images. • Our bottom-up framework aggregates and transforms per-frame 3D Gaussian Splats into a cohesive scene representation, enabling self-supervised motion estimation. Furthermore, we introduce motion tokens that capture common motion primitives and regularize motion predictions, facilitating dynamic motion group segmentation without explicit motion or correspondence supervision. • We present several enhancements for in-the-wild scenarios, including sky modeling, camera exposure inconsistency handling, large novel-view extrapolation, and fine-grained human motions reconstruction, making STORM well-suited for real-world applications.
0:31

Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Contributions: • We propose STORM, the first feed-forward, self-supervised method for fast and accurate reconstruction of dynamic 3D scenes from sparse, multi-timestep, posed camera images. • Our bottom-up framework aggregates and transforms per-frame 3D Gaussian Splats into a cohesive scene representation, enabling self-supervised motion estimation. Furthermore, we introduce motion tokens that capture common motion primitives and regularize motion predictions, facilitating dynamic motion group segmentation without explicit motion or correspondence supervision. • We present several enhancements for in-the-wild scenarios, including sky modeling, camera exposure inconsistency handling, large novel-view extrapolation, and fine-grained human motions reconstruction, making STORM well-suited for real-world applications.

MrNeRF

53,292 Aufrufe • vor 1 Jahr

I flipped through 300 pages of deep learning math puzzles by hand ✍️ This is the proof copy of the "Deep Learning Math Workbook" I made to help you learn and practice 12 foundational math concepts below👇
0:25

I flipped through 300 pages of deep learning math puzzles by hand ✍️ This is the proof copy of the "Deep Learning Math Workbook" I made to help you learn and practice 12 foundational math concepts below👇

Tom Yeh

2,378,310 Aufrufe • vor 1 Jahr

Self-supervised representation learning looks a bit like RL. What if we literally use RL as a SSL method for visual representations? Turns out that it works quite well. In new work by Dibya Ghosh, we show how this can be done:
1:09

Self-supervised representation learning looks a bit like RL. What if we literally use RL as a SSL method for visual representations? Turns out that it works quite well. In new work by Dibya Ghosh, we show how this can be done:

Sergey Levine

48,715 Aufrufe • vor 1 Jahr

Tesla Full Self-Driving (Supervised) 13.2 exits Universal Studios
1:05

Tesla Full Self-Driving (Supervised) 13.2 exits Universal Studios

Whole Mars Catalog

117,580 Aufrufe • vor 1 Jahr

Tesla Full Self-Driving (Supervised) 13.2.8 is the best self-driving system I've ever seen
3:43

Tesla Full Self-Driving (Supervised) 13.2.8 is the best self-driving system I've ever seen

Whole Mars Catalog

82,414 Aufrufe • vor 1 Jahr

My one year of self learning animation TT
1:27

My one year of self learning animation TT

Lunacy(COMMS PAUSED)💜💔🐢⏳

22,970 Aufrufe • vor 5 Monaten

A year of growth, development and learning. The final episode of Building Dreams pres. by Self Financial Inc drops tomorrow 🎥
0:28

A year of growth, development and learning. The final episode of Building Dreams pres. by Self Financial Inc drops tomorrow 🎥

San Antonio Spurs

28,025 Aufrufe • vor 1 Tag

In 2019, Elon said HW3 was enough for Full Self-Driving. Seven years later, it needs to be Supervised by a human due to safety concerns. Tesla calls it Full Self-Driving Supervised, because they know it will make dangerous maneuvers at any given moment.
0:20

In 2019, Elon said HW3 was enough for Full Self-Driving. Seven years later, it needs to be Supervised by a human due to safety concerns. Tesla calls it Full Self-Driving Supervised, because they know it will make dangerous maneuvers at any given moment.

Miss Jilianne

14,891 Aufrufe • vor 2 Monaten

Free Machine Learning with Python Course from IBM Topic covered: - Supervised Learning - Unsupervised Learning - Dimensionality Reduction & Collaborative Filtering 100% FREE Course link 🧵👇
0:34

Free Machine Learning with Python Course from IBM Topic covered: - Supervised Learning - Unsupervised Learning - Dimensionality Reduction & Collaborative Filtering 100% FREE Course link 🧵👇

Afiz ⚡️

59,880 Aufrufe • vor 3 Jahren

Eric Jang weighs in on RL vs. supervised learning for humanoid robot manipulation tasks.
1:40

Eric Jang weighs in on RL vs. supervised learning for humanoid robot manipulation tasks.

The Humanoid Hub

10,656 Aufrufe • vor 11 Monaten