Abstract: This paper presents a novel approach for object classification and pose estimation which employs spherical light field rendering to generate virtual views based on synthe...
This contribution addresses the problem of obtaining 3D models from image sequences. A 3D surface description of the scene is extracted completely from a set of uncalibrated camer...
We present an approach to convert a small portion of a light field with extracted depth information into a cinematic effect with simulated, smooth camera motion that exhibits a se...
Ke Colin Zheng, Alex Colburn, Aseem Agarwala, Mane...
This paper presents a method for joint stereo matching and object segmentation. In our approach a 3D scene is represented as a collection of visually distinct and spatially cohere...
Michael Bleyer, Carsten Rother, Pushmeet Kohli, Da...
This paper describes a computationally feasible approximation to the AIXI agent, a universal reinforcement learning agent for arbitrary environments. AIXI is scaled down in two ke...
Joel Veness, Kee Siong Ng, Marcus Hutter, William ...