4.3k citations · 19.2k across the 101 of their papers we have counts for
9 papers · 2 filters
MSeg: A Composite Dataset for Multi-domain Semantic Segmentation
John Lambert, Zhuang Liu, Ozan Sener +2
We present MSeg, a composite dataset that unifies semantic segmentation datasets from different domains. A naive merge of the constituent datasets yields poor performance due to in…
Shape from Polarization for Complex Scenes in the Wild
Chenyang Lei, Chenyang Qi, Jiaxin Xie +3
We present a new data-driven approach with physics-based priors to scene-level normal estimation from a single polarization image. Existing shape from polarization (SfP) works main…
Non-deep Networks
Ankit Goyal, Alexey Bochkovskiy, Jia Deng +1
Depth is the hallmark of deep neural networks. But more depth means more sequential computation and higher latency. This begs the question -- is it possible to build high-performin…
ASH: A Modern Framework for Parallel Spatial Hashing in 3D Perception
Wei Dong, Yixing Lao, Michael Kaess +1
We present ASH, a modern and high-performance framework for parallel spatial hashing on GPU. Compared to existing GPU hash map implementations, ASH achieves higher performance, sup…
Enhancing Photorealism Enhancement
Stephan R. Richter, Hassan Abu AlHaija, Vladlen Koltun
We present an approach to enhancing the realism of synthetic images. The images are enhanced by a convolutional network that leverages intermediate representations produced by conv…
Vision Transformers for Dense Prediction
René Ranftl, Alexey Bochkovskiy, Vladlen Koltun
We introduce dense vision transformers, an architecture that leverages vision transformers in place of convolutional networks as a backbone for dense prediction tasks. We assemble…