• Publications
  • Influence
Scale-Space and Edge Detection Using Anisotropic Diffusion
TLDR
A new definition of scale-space is suggested, and a class of algorithms used to realize a diffusion process is introduced, chosen to vary spatially in such a way as to encourage intra Region smoothing rather than interregion smoothing. Expand
A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
TLDR
A database containing 'ground truth' segmentations produced by humans for images of a wide variety of natural scenes is presented and an error measure is defined which quantifies the consistency between segmentations of differing granularities. Expand
Shape matching and object recognition using shape contexts
TLDR
This paper presents work on computing shape models that are computationally fast and invariant basic transformations like translation, scaling and rotation, and proposes shape detection using a feature called shape context, which is descriptive of the shape of the object. Expand
Learning to detect natural image boundaries using local brightness, color, and texture cues
TLDR
The two main results are that cue combination can be performed adequately with a simple linear model and that a proper, explicit treatment of texture is required to detect boundaries in natural images. Expand
SlowFast Networks for Video Recognition
TLDR
This work presents SlowFast networks for video recognition, which achieves strong performance for both action classification and detection in video, and large improvements are pin-pointed as contributions by the SlowFast concept. Expand
End-to-End Recovery of Human Shape and Pose
TLDR
This work introduces an adversary trained to tell whether human body shape and pose parameters are real or not using a large database of 3D human meshes, and produces a richer and more useful mesh representation that is parameterized by shape and 3D joint angles. Expand
Large Displacement Optical Flow: Descriptor Matching in Variational Motion Estimation
  • T. Brox, Jitendra Malik
  • Mathematics, Medicine
  • IEEE Transactions on Pattern Analysis and Machine…
  • 1 March 2011
TLDR
A way to approach the problem of dense optical flow estimation by integrating rich descriptors into the variational optical flow setting, while reaching out to new domains of motion analysis where the requirement of dense sampling in time is no longer satisfied is presented. Expand
Learning Rich Features from RGB-D Images for Object Detection and Segmentation
TLDR
A new geocentric embedding is proposed for depth images that encodes height above ground and angle with gravity for each pixel in addition to the horizontal disparity to facilitate the use of perception in fields like robotics. Expand
Spectral grouping using the Nystrom method
TLDR
The contribution of this paper is a method that substantially reduces the computational requirements of grouping algorithms based on spectral partitioning making it feasible to apply them to very large grouping problems. Expand
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