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Explore implicit neural scene representations with Vincent Sitzmann from Stanford. Learn about 3D reconstruction, meta-learning, and semantic segmentation in less than an hour.
Explore Neural Radiance Fields for view synthesis with Matthew Tancik from UC Berkeley in this short seminar by Autonomous Vision Group. Learn about volumetric rendering, network parameterization, and more.
Explore 3D scene understanding with Google Brain's Andrea Tagliasacchi in this under 1-hour seminar by Autonomous Vision Group. Learn about permutation equivariant learning, digital human representation, and 3D geometry.
Explore the perceptual abilities of unsupervised object-centric learning approaches with Andreas Geiger's keynote. Learn about detection, segmentation, and tracking in less than an hour.
Explore 3D controllable image synthesis with Andreas Geiger's keynote, focusing on Generative Adversarial Networks and their potential to replace classical rendering pipelines.
Explore the robustness of optical flow networks against adversarial attacks in self-driving cars with Andreas Geiger's keynote. Less than 1-hour workload.
Andreas Geiger's keynote on robust driving policies offers state-of-the-art performance insights in CARLA simulator, situational driving policy framework, and novel approaches to covariate shift in imitation learning.
Andreas Geiger's short keynote on 3D reconstruction in function space, explores neural implicit 3D representations, their abilities, limitations, and application in 3D geometry and textured models.
Andreas Geiger's keynote on Implicit Neural Representations offers insights into 3D reconstruction, object and scene-level reconstruction, and light manipulation. Less than 1hr workload.
Explore neural implicit 3D representations with Andreas Geiger in under an hour. Learn about reconstructing 3D geometry, textured models, and motion using 2D supervision.
Explore Andreas Geiger's insights on using semantic segmentation for autonomous driving, focusing on annotation efficiency and driving performance trade-offs. Less than 1-hour workload.
Explore 3D reconstruction in function space with Andreas Geiger in less than an hour. Dive into neural implicit models, occupancy networks, and more.
Explore the evolution of human motion estimation with Andreas Geiger, delving into computer vision, kinematic trees, and graphical models. Workload: 1-2 hours.
Explore the central-peripheral dichotomy in visual decoding with Zhaoping Li in this 1-2 hour material by Andreas Geiger. Dive into vision, selection, and stereo vision.
Learn robust scene analysis techniques with Stefan Roth in less than an hour, offered by Andreas Geiger. Gain insights into optical flow estimation, motion segmentation, and uncertainty sources.
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