Program Overview

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Introduction to the Department of Electrical Engineering and Computer Sciences (EECS) at UC Berkeley

The Department of Electrical Engineering and Computer Sciences (EECS) at UC Berkeley offers one of the strongest research and instructional programs in this field anywhere in the world.

Academics

Undergraduate Admissions & Programs

• CS Major
• EECS Major
• EECS/CS Program Comparison Chart
• Second Bachelor's Degree
• Summer Research
• Cal Day

Graduate Admissions & Programs

• Grad Admissions FAQ
• Industry-Oriented Programs
• Research-Oriented Programs
• Fellowships
• Adding the EECS/CS M.S. From Another Department
• Recommended Coursework

Courses

• EE Courses
• CS Courses

Research

Research Overview

Research is the foundation of Berkeley EECS. Faculty, students, and staff work together on cutting-edge projects that cross disciplinary boundaries to improve everyday life and make a difference.

Areas

• Artificial Intelligence (AI)
• Biosystems & Computational Biology (BIO)
• Graphics (GR)

Centers & Labs

• Various centers and labs are available for research purposes.

People

Faculty

• In Memoriam

Students

• Student Awards
• Student Organizations

Staff

• Student Affairs
• Faculty Support
• Course Support
• Facilities and Engineering Services
• Financial Services
• HR
• IT Support
• Industrial & Public Relations

Alumni

• EE Distinguished Alumni
• CS Distinguished Alumni

CS C280: Computer Vision

Catalog Description

Paradigms for computational vision. Relation to human visual perception. Mathematical techniques for representing and reasoning, with curves, surfaces and volumes. Illumination and reflectance models. Color perception. Image segmentation and aggregation. Methods for bottom-up three dimensional shape recovery: Line drawing analysis, stereo, shading, motion, texture. Use of object models for prediction and recognition.

Units

3

Also Offered As

VIS SCI C280

Related Areas

• Artificial Intelligence (AI)
• Biosystems & Computational Biology (BIO)
• Graphics (GR)

Prerequisites

MATH 51; MATH 52; MATH 53; and MATH 54. (Knowledge of linear algebra and calculus).

Formats

• Spring: 3.0 hours of lecture per week
• Fall: 3.0 hours of lecture per week

Grading Basis

Letter

Final Exam Status

Written final exam conducted during the scheduled final exam period

Class Schedule (Spring 2026)

CS C280 – TuTh 15:30-16:59, Hearst Mining 390 – Alexei Efros, Angjoo Kanazawa

Class Notes

• Time conflicts are not allowed
• Interested non-EECS/CS PhD students will be vetted by the instructors. Please attend the first class meeting for further instructions.