Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead
of capturing images at a fixed rate, they asynchronously measure per-pixel brightness …

Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

We present a unified formulation and model for three motion and 3D perception tasks:
optical flow, rectified stereo matching and unrectified stereo depth estimation from posed …

Most online multi-object trackers perform object detection stand-alone in a neural net without
any input from tracking. In this paper, we present a new online joint detection and tracking …

Self-supervised monocular depth estimation networks are trained to predict scene depth
using nearby frames as a supervision signal during training. However, for many …

In this paper, we present TransMVSNet, based on our exploration of feature matching in
multi-view stereo (MVS). We analogize MVS back to its nature of a feature matching task and …

We present PatchmatchNet, a novel and learnable cascade formulation of Patchmatch for
high-resolution multi-view stereo. With high computation speed and low memory …

We present a method for novel view synthesis from input images that are freely distributed
around a scene. Our method does not rely on a regular arrangement of input views, can …

Recent neural view synthesis methods have achieved impressive quality and realism,
surpassing classical pipelines which rely on multi-view reconstruction. State-of-the-Art …

Abstract We present Stable View Synthesis (SVS). Given a set of source images depicting a
scene from freely distributed viewpoints, SVS synthesizes new views of the scene. The …