Course Description: This seminar will explore and analyze the current literature in computer vision, especially focusing on computational methods for visual recognition. Our topics include image classification and understanding, object detection, image segmentation, and other high-level perceptual tasks. Particularly, we will explore this semester recent topics such as Multimodal LLMs, Controllable Diffusion Models, LLMs for Grounded tasks in Vision and Robotics, Diffusion Models for Video, Transformer Models for Image Matching, among others.

Recommended Prerrequisites: COMP 547 (Computer Vision) or COMP 646 (Deep Learning for Vision and Language) or COMP 546/ELEC 546 (Intro to Computer Vision) or COMP 576 (Intro to Deep Learning) or COMP 647 (Deep Learning) or research experience in any of these topics.

Disclaimer: The topics on this list are tentative and subject to adjustments throughout the semester as interests in the group evolve.

Logistics: This is a seminar with a pass/fail grade. Registered students are required to participate and present a recent work in a topic of interest of the seminar at least once throughout the semester and complete and original research project and final research report. A Satisfactory grade requires participating presenting a paper at least once during the semester, actively participating in discussions throughout the semester, and completing the project.

Honor Code and Academic Integrity: "In this course, all students will be held to the standards of the Rice Honor Code, a code that you pledged to honor when you matriculated at this institution. If you are unfamiliar with the details of this code and how it is administered, you should consult the Honor System Handbook at http://honor.rice.edu/honor-system-handbook/. This handbook outlines the University's expectations for the integrity of your academic work, the procedures for resolving alleged violations of those expectations, and the rights and responsibilities of students and faculty members throughout the process."

Title IX Support: Rice University cares about your wellbeing and safety. Rice encourages any student who has experienced an incident of harassment, pregnancy discrimination or gender discrimination or relationship, sexual, or other forms interpersonal violence to seek support through The SAFE Office. Students should be aware when seeking support on campus that most employees, including myself, as the instructor/TA, are required by Title IX to disclose all incidents of non-consensual interpersonal behaviors to Title IX professionals on campus who can act to support that student and meet their needs. For more information, please visit safe.rice.edu or email titleixsupport@rice.edu.

Disability Resource Center: "If you have a documented disability or other condition that may affect academic performance you should: 1) make sure this documentation is on file with the Disability Resource Center (Allen Center, Room 111 / adarice@rice.edu / x5841) to determine the accommodations you need; and 2) talk with me to discuss your accommodation needs."