Autonomous driving vehicles require both a precise localization and mapping solution in
different driving environment. In this context, Simultaneous Localization and Mapping …

With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual
(RGB) sensing has become available for widespread use. The complementary nature of the …

Large pretrained (eg," foundation") models exhibit distinct capabilities depending on the
domain of data they are trained on. While these domains are generic, they may only barely …

Deep generative models are becoming increasingly powerful, now generating diverse high
fidelity photo-realistic samples given text prompts. Have they reached the point where …

Neural graphics primitives, parameterized by fully connected neural networks, can be costly
to train and evaluate. We reduce this cost with a versatile new input encoding that permits …

Estimating the accurate depth from a single image is challenging since it is inherently
ambiguous and ill-posed. While recent works design increasingly complicated and powerful …

Neural radiance fields (NeRF) encode a scene into a neural representation that enables
photo-realistic rendering of novel views. However, a successful reconstruction from RGB …

Neural volume rendering became increasingly popular recently due to its success in
synthesizing novel views of a scene from a sparse set of input images. So far, the geometry …

The goal of this work is to perform 3D reconstruction and novel view synthesis from data
captured by scanning platforms commonly deployed for world mapping in urban outdoor …

Synthesizing photo‐realistic images and videos is at the heart of computer graphics and has
been the focus of decades of research. Traditionally, synthetic images of a scene are …