Conference

Doctoral Consortium

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Doctoral Consortium Supported by: Call for Participation: CVPR 2026 Doctoral Consortium Overview The Doctoral Consortium provides a unique opportunity for students, who are close to finishing or who have recently finished their doctorate, to interact with experienced researchers in computer vision. A senior member of the community will be assigned as a mentor for each student based on the student's preference or similarity of research interests. All students and mentors will attend a Doctoral Consortium event during the conference (in-person), allowing the students to discuss their ongoing research and career plans with their mentor. In addition, each student will present a poster, either describing their thesis research or a single recent paper, to the other participants and their mentors. Eligibility Students must be conducting research in computer vision and be within 6 months (before or after) of graduating with their doctoral degree. Submission Guidelines Students who meet the eligibility requirements should apply at https://openreview.net/group?id=thecvf.com/CVPR/2026/Doctoral_Consortium . The applicant must submit the following as a single PDF file: The applicant's CV. A one-page statement summarizing the aspects of the candidate’s research that they are most excited about and why they think they are a good candidate for the Doctoral Consortium event. A signed letter from their advisor confirming the actual / estimated date of graduation. The candidate’s Google Scholar link Additional information will be requested via the submission form. Please ensure that all pieces of information are included in the application. Incomplete applications will be rejected. Review Process If all applications cannot be supported, selection will be based on the provided material and the student's graduation date, and supporting a diverse collection of students across institutions and research areas. Travel Awards The amount is yet to be determined, but will likely include a waiver for conference registration fees and some travel funding. Travel reimbursements will cover part of the expenses. The awards will be in the form of a reimbursement check you will receive after the conference, and after you submit forms/receipts. Detailed instructions will be provided separately after the conference if you are at a non-US institution. Poster Format Please refer to the general CVPR 2026 guidelines; the Doctoral Consortium will use the same format. During the actual event, please use any available poster board in the designated Doctoral Consortium room. No poster numbers will be assigned. Important Dates Submission deadline: Apr 13, 2026 Notification of acceptance: Apr 27, 2026 (estimated) Doctoral Consortium event: TBD Contact Abby Stylianou, Saint Louis University, abby.stylianou@slu.edu Paola Cascante Bonilla , Stony Brook University, paola.cascantebonilla@stonybrook.edu Successful Page Load

Executive Summary

The CVPR 2026 Doctoral Consortium provides a unique opportunity for computer vision students to interact with experienced researchers and present their research, while receiving mentorship and potential travel awards. To be eligible, students must be close to finishing or have recently finished their doctorate, with a focus on computer vision research. The application process involves submitting a CV, research statement, and advisor confirmation, with a review process prioritizing diversity and research areas. Key dates include a submission deadline of April 13, 2026, and estimated notification of acceptance by April 27, 2026. This event aims to facilitate networking, research discussion, and career planning for the next generation of computer vision researchers.

Key Points

  • The CVPR 2026 Doctoral Consortium offers a unique opportunity for computer vision students to interact with experienced researchers.
  • Eligibility requirements include being close to finishing or having recently finished a doctorate in computer vision research.
  • The application process involves submitting a CV, research statement, and advisor confirmation.
  • A review process prioritizes diversity and research areas across institutions.
  • Travel awards may include a waiver for conference registration fees and travel funding.

Merits

Promotes Networking and Collaboration

The Doctoral Consortium facilitates interactions between students and experienced researchers, fostering a collaborative environment for sharing ideas and knowledge.

Supports Career Development

The event provides a platform for students to discuss their research and career plans with mentors, aiding in their professional growth and development.

Diversifies Research Areas

The review process prioritizes supporting a diverse collection of students across institutions and research areas, promoting a well-rounded representation of the field.

Demerits

Limited Geographic Representation

The event's focus on computer vision research may lead to a predominantly North American or Western representation, potentially limiting the diversity of participating students.

Unclear Travel Award Details

The amount of travel funding and reimbursement details are unclear, potentially causing uncertainty for students from non-US institutions.

Expert Commentary

The CVPR 2026 Doctoral Consortium represents a valuable initiative for computer vision students, offering a unique opportunity for networking, research discussion, and career planning. While some limitations, such as geographic representation and travel award details, exist, the event's focus on diversity and research areas is commendable. As the field of computer vision continues to evolve, initiatives like this consortium will play a crucial role in shaping the next generation of researchers and promoting a more inclusive research community.

Recommendations

  • Future iterations of the Doctoral Consortium should prioritize increasing geographic representation and providing clearer travel award details.
  • The event organizers should consider expanding the scope of the consortium to include other areas of computer science, fostering a broader networking opportunity for students.

Sources

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