Reconstruction of general dynamic scenes is motivated by potential applications in film and broadcast production together with the ultimate goal of automatic understanding of real-world scenes from distributed camera networks. With recent advances in hardware and the advent of virtual and augmented reality, dynamic scene reconstruction is being applied to more complex scenes with applications in Entertainment, Games, Film, Creative Industries and AR/VR/MR. We welcome contributions to this workshop in the form of oral presentations and posters. Suggested topics include, but are not limited to:
- - Dynamic 3D reconstruction from single, stereo or multiple views
- - Learning-based methods in dynamic scene reconstruction and understanding
- - Multi-modal dynamic scene modelling (RGBD, LIDAR, 360 video, light fields)
- - 4D reconstruction and modelling
- - 3D/4D data acquisition, representation, compression and transmission
- - Scene analysis and understanding in 2D and 3D
- - Structure from motion, camera calibration and pose estimation
- - Digital humans: motion and performance capture, bodies, faces, hands
- - Geometry processing
- - Computational photography
- - Appearance and reflectance modelling
- - Scene modelling in the wild, moving cameras, handheld cameras
- - Applications of dynamic scene reconstruction (VR/AR, character animation, free-viewpoint video, relighting, medical imaging, creative content production, animal tracking, HCI, sports)
The objectives for this workshop are to:
- - Bringing together leading experts in the field of general dynamic scene reconstruction to help propel the field forward.
- - Create and maintain an online database of datasets and papers
- - Accelerate research progress in the field of dynamic scene reconstruction to match the requirements of real-world applications by identifying the challenges and ways to address them through a panel discussion between experts, presenters and attendees.
We welcome submissions from both industry and academia, including interdisciplinary work and work from those outside of the mainstream computer vision community.
Papers will be limited up to 8 pages according to the CVPR format (main conference authors guidelines). All papers will be reviewed with double blind policy. Papers will be selected based on relevance, significance and novelty of results, technical merit, and clarity of presentation.
|Paper submission deadline||March 16, 2020|
|Notification to authors||March 30, 2020|
|Camera ready deadline||April 13, 2020|
The best paper will receive a NVIDIA TITAN RTX GPU, courtesy of our workshop sponsor NVIDIA.