Robust16
* *Robust Features for Computer Vision
* Background Subtraction Using Local SVD Binary Pattern
* Best of Both Worlds: Combining Data-Independent and Data-Driven Approaches for Action Recognition, The
* Deep Features or Not: Temperature and Time Prediction in Outdoor Scenes
* Deeply Exploit Depth Information for Object Detection
* Do We Need Binary Features for 3D Reconstruction?
* Efficient Deep Feature Learning and Extraction via StochasticNets
* Embedding Sequential Information into Spatiotemporal Features for Action Recognition
* Euclidean and Hamming Embedding for Image Patch Description with Convolutional Networks
* Fast Image Gradients Using Binary Feature Convolutions
* Generating Discriminative Object Proposals via Submodular Ranking
* Improving Gradient Histogram Based Descriptors for Pedestrian Detection in Datasets with Large Variations
* Learning Discriminative Features with Class Encoder
* Robust 2DPCA and Its Application
* Texture Complexity Based Redundant Regions Ranking for Object Proposal
* Unsupervised Robust Feature-Based Partition Ensembling to Discover Categories
16 for Robust16
Robust90
* *International Conference on Robust Computer Vision
* Algebraic Procedure for the Computation of Optical Flow from First Order Derivatives of the Image Brightness, An
* Analysis of Different Robust Methods for Pose Refinement
* Dense Depth Maps from 2-D Cepstrum Matching of Image Sequences
* Developing Robust Techniques for Computer Vision
* Efficient, Linear, Sequential Formulation for Motion Estimation from Noisy Data, An
* Fitting Curves with Discontinuities
* Generalized Minimum Volume Ellipsoid Clustering with Applications in Computer Vision
* Non-Linear Filtering for Chaincoded Contours
* On Robust Edge Detection
* Probabilistic Hough Transform, A
* Robust Computational Vision
* Robust Dynamic Stereo for Incremental Disparity Map Refinement
* Robust Method for Surface Reconstruction, A
* Robust Motion Estimation Using Stereo Vision
* Robust Obstacle Detection Using Optical Flow
* Robust Recovery of Precursive Polynomial Image Structure
* Robust Vision-Programs Based on Statistical Feature Measurements
* Using Geometrical Rules and a Priori Knowledge for the Understanding of Indoor Scenes
* What's in a Set of Points?
20 for Robust90
Robust94
* Diagnostics and Performance Evaluation in Computer Vision