Winter 2026–27 — Sundays. Lecture 13:30–16:30, Tutorial 16:30–17:30.
Planned schedule: 13 teaching Sundays, one more than Spring 2026. The first 12 lecture topics keep their previous order; the January 24 session is reserved.
Tutorials: the eleven Spring 2026 tutorials retain their order, beginning with PyTorch + Point Ops on November 1. A new Vision-Language Models (VLMs) tutorial is scheduled for January 17. One lecture and one tutorial remain unassigned on January 24.
Materials: Winter 2026–27 slides and recordings will be posted here as the semester progresses. The simulations below remain available.
Previous semester: The Spring 2026 schedule, including its slides and recordings, is a useful reference. The course content is very similar, but may not match this semester exactly.
Assignments: release and due dates below are provisional. Winter assignment packages and submission links will be posted when released. Project deadlines are to be announced.
Lecture and tutorial times are carried over from Spring 2026, pending confirmation. Dates follow the current Technion academic calendar. December 6 is a teaching day; the Hanukkah break is December 9–11.
| Wk | Date | Lecture | Tutorial | Planned assignments | Resources |
|---|---|---|---|---|---|
| 1 | Basics of Imaging | PyTorch + Point Ops |
HW 1
Theory
From Scratch
Applied
|
Lecture Slides (PDF, from previous semester) 📹 Lecture Recording (from previous semester) Conv 1D Demo Filters 2D Demo Lens & Focus Demo |
|
| 2 | ML Basics | Linear Classification |
Lecture Slides (PDF) 📹 Lecture Recording |
||
| 3 | Neural Networks | PyTorch Autograd |
HW 2
Theory
From Scratch
Applied
|
Lecture Slides (PDF) | |
| 4 | Frequencies & Sampling | Image Pyramids |
FT Explorer FT Explorer 2D FT Filter Explorer Resize Simulation |
||
| 5 | CNNs | Adversarial Examples |
HW 3
Theory
From Scratch
Applied
|
— | |
| 6 | Training & Architectures | Transformers | Optimizers Demo | ||
| 7 | Geometry & 3D | Deep 3D |
3D Reconstruction Demo 3D Representations Demo LiDAR Demo Octree Demo PointNet Demo |
||
| 8 | Motion + Localization | Detection and Segmentation |
HW 4
Theory
From Scratch
Applied
|
Coarse-to-Fine LK Demo | |
| 9 | Generative Models 1 | Text to Image | — | ||
| 10 | Generative Models 2 | Generative Image Editing |
HW 5
Theory
From Scratch
Applied
|
— | |
| 11 | Self-Supervision + Interpretability | Efficiency | — | ||
| 12 | Neural Rendering | Vision-Language Models (VLMs) | HW 5 dueFinal project period → | — | |
| 13 | Additional session — topic to be announced | To be announced | — | — |