When: January 4th or 5th, 2027
Time: TBA
Where: Buena Vista, Florida, WACV 2027
Location: Disney Springs, room: TBA
Schedule (tentative)
9:00 Opening
9:05 Invited Talk I
9:35 Invited Talk II
10:05 Posters
11:15 Coffee Break
11:30 Invited Talk III
12:00 Invited Talk IV
12:30 Closing
The workshop will feature a poster session with contributed papers.
OpenReview submission system: TBA
Paper submission deadline: TBA
Decisions: TBA
Camera Ready Deadline: TBA
Papers accepted to the workshop will be published in the WACV 2027 workshop proceedings.
Paper submissions should use the WACV 2027 paper template and follow the WACV 2027 guidelines. In particular, paper submissions cannot be longer than 8 pages (excluding references).
Camera calibration is the problem of estimating the parameters of the projective mapping from 3D scene points to pixels in an image (or the inverse mapping from pixels to 3D rays in the scene). Camera pose estimation is the problem of determining the camera pose, i.e., the position and orientation, for a given image (or the relative pose between two images). (Nearly) all advanced 3D computer vision algorithms, including 3D reconstruction via NeRFs or 3D Gaussian splatting, as well as 3D scene understanding, require known camera calibrations and poses. Calibration and pose estimation are also crucial problems in industry. In order to use cameras for downstream tasks such as tracking, recognition, segmentation, detection, navigation, etc., the cameras have to be calibrated. Moreover, industry often requires the calibration of special systems of cameras or other sensors, for which standard solutions are not directly applicable.
The accuracy of the calibrations and the poses strongly impact the overall performance of these algorithms. Improving the accuracy, robustness, and efficiency of calibration and pose estimation methods can open doors to new applications, e.g., using advanced multi-camera systems in the space industry and for medical applications. However, most researchers do not concern themselves with accurate calibration. They either use calibrations and poses provided by a dataset, or use software such as COLMAP to compute them. The software is typically treated as a black box, with limited understanding about the accuracy of the results. At the same time practically relevant, research on calibration and pose estimation of such multi-sensor systems is usually considered as not sufficiently novel to be published at the top-tier conferences.
The goals of the workshop are: 1) Offer a forum for researchers working on classical approaches and learning-based approaches to meet and exchange ideas, with the aim of bringing both sub-communities closer together. This is facilitated through invited talks. 2) Provide researchers and practitioners using camera calibration and pose estimation algorithms as black box tools the opportunity to learn about the current state-of-the-art and open problems in the field. 3) Provide researchers working on camera calibration and pose estimation methods a platform that, unlike the main conference, focuses on their research topics. To this end, our workshop invites the submission of novel, unpublished research in the form of paper submissions.
The first edition of this workshop was held at ICCV 2025.
We invite original research contributions in (but not limited to) the following areas:
Classical methods for camera calibration and camera (relative or absolute) pose estimation.
Learning-based methods for camera calibration and camera (relative or absolute) pose estimation.
Efficient, feedforward approaches to camera calibration and / or camera pose estimation.
Calibration of multi-camera and other multi-modal sensor systems.
Pose estimation from multiple/different modalities (images, depths, event cameras, etc.).
Combining classical and learning-based approaches for calibration and pose estimation.
Applications of camera calibration and camera pose estimation methods.
New theories on (learning-based) camera calibration and/or camera pose estimation.
Analysis of open challenges in the areas of calibration and/or pose estimation.
Datasets and benchmarks for related tasks.
We will only accept full paper submissions (5 pages or longer, excluding references). All submissions will be peer-reviewed and, if accepted, published in the WACV 2027 workshop proceedings. All submissions need to describe novel work and cannot be under review, accepted, or published at another venue.