4.3k citations · 19.2k across the 101 of their papers we have counts for
8 papers · 2 filters
Point Transformer
Hengshuang Zhao, Li Jiang, Jiaya Jia +2
Self-attention networks have revolutionized natural language processing and are making impressive strides in image analysis tasks such as image classification and object detection.…
Stable View Synthesis
Gernot Riegler, Vladlen Koltun
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 method operat…
NeRF++: Analyzing and Improving Neural Radiance Fields
Kai Zhang, Gernot Riegler, Noah Snavely +1
Neural Radiance Fields (NeRF) achieve impressive view synthesis results for a variety of capture settings, including 360 capture of bounded scenes and forward-facing capture of bou…
Free View Synthesis
Gernot Riegler, Vladlen Koltun
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 syn…
High-dimensional Convolutional Networks for Geometric Pattern Recognition
Christopher Choy, Junha Lee, Rene Ranftl +2
Many problems in science and engineering can be formulated in terms of geometric patterns in high-dimensional spaces. We present high-dimensional convolutional networks (ConvNets)…
Deep Global Registration
Christopher Choy, Wei Dong, Vladlen Koltun
We present Deep Global Registration, a differentiable framework for pairwise registration of real-world 3D scans. Deep global registration is based on three modules: a 6-dimensiona…
Exploring Self-attention for Image Recognition
Hengshuang Zhao, Jiaya Jia, Vladlen Koltun
Recent work has shown that self-attention can serve as a basic building block for image recognition models. We explore variations of self-attention and assess their effectiveness f…
Tracking Objects as Points
Xingyi Zhou, Vladlen Koltun, Philipp Krähenbühl
Tracking has traditionally been the art of following interest points through space and time. This changed with the rise of powerful deep networks. Nowadays, tracking is dominated b…