activity
20122022
most citedEfficient Inference in Fully Connected CRFs with Gaussian Edge Potentials

3k citations · 3.4k across the 8 of their papers we have counts for

collaborators

18 papers

cs.CV2022

Global Tracking Transformers

Xingyi Zhou, Tianwei Yin, Vladlen Koltun +1

We present a novel transformer-based architecture for global multi-object tracking. Our network takes a short sequence of frames as input and produces global trajectories for all o…

cs.CV2021

Towards Long-Form Video Understanding

Chao-Yuan Wu, Philipp Krähenbühl

Our world offers a never-ending stream of visual stimuli, yet today's vision systems only accurately recognize patterns within a few seconds. These systems understand the present,…

cs.RO2021

Learning to drive from a world on rails

Dian Chen, Vladlen Koltun, Philipp Krähenbühl

We learn an interactive vision-based driving policy from pre-recorded driving logs via a model-based approach. A forward model of the world supervises a driving policy that predict…

cs.CV2021162 cited

Probabilistic two-stage detection

Xingyi Zhou, Vladlen Koltun, Philipp Krähenbühl

We develop a probabilistic interpretation of two-stage object detection. We show that this probabilistic interpretation motivates a number of common empirical training practices. I…

eess.IV202029 cited

Lossless Image Compression through Super-Resolution

Sheng Cao, Chao-Yuan Wu, Philipp Krähenbühl

We introduce a simple and efficient lossless image compression algorithm. We store a low resolution version of an image as raw pixels, followed by several iterations of lossless su…

cs.CV2020

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…