157 citations · 296 across the 11 of their papers we have counts for
6 papers · 1 filter
Hierarchical Deep Stereo Matching on High-resolution Images
Gengshan Yang, Joshua Manela, Michael Happold +1
We explore the problem of real-time stereo matching on high-res imagery. Many state-of-the-art (SOTA) methods struggle to process high-res imagery because of memory constraints or…
Inferring Distributions Over Depth from a Single Image
Gengshan Yang, Peiyun Hu, Deva Ramanan
When building a geometric scene understanding system for autonomous vehicles, it is crucial to know when the system might fail. Most contemporary approaches cast the problem as dep…
Learning to Optimally Segment Point Clouds
Peiyun Hu, David Held, Deva Ramanan
We focus on the problem of class-agnostic instance segmentation of LiDAR point clouds. We propose an approach that combines graph-theoretic search with data-driven learning: it sea…
Argoverse: 3D Tracking and Forecasting with Rich Maps
Ming-Fang Chang, John Lambert, Patsorn Sangkloy +8
We present Argoverse -- two datasets designed to support autonomous vehicle machine learning tasks such as 3D tracking and motion forecasting. Argoverse was collected by a fleet of…
Learning to Track Any Object
Achal Dave, Pavel Tokmakov, Cordelia Schmid +1
Object tracking can be formulated as "finding the right object in a video". We observe that recent approaches for class-agnostic tracking tend to focus on the "finding" part, but l…
Photo-Sketching: Inferring Contour Drawings from Images
Mengtian Li, Zhe Lin, Radomir Mech +2
Edges, boundaries and contours are important subjects of study in both computer graphics and computer vision. On one hand, they are the 2D elements that convey 3D shapes, on the ot…