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Found 33 papers, 14 papers with code
Stress-Testing LiDAR Registration
The standard benchmark for this setting, KITTI-10m, has essentially been saturated by recent algorithms: many of them achieve near-perfect recall.
How Low Can We Go? Pixel Annotation for Semantic Segmentation
Based on this single-image-annotation experiment, we design an experiment to quickly annotate an entire data set.
Transformaly -- Two (Feature Spaces) Are Better Than One
Anomaly detection is a well-established research area that seeks to identify samples outside of a predetermined distribution.
Ranked #1 on
Anomaly Detection
on One-class CIFAR-100
(using extra training data)
Adversarial Mask: Real-World Adversarial Attack Against Face Recognition Models
In addition, we validated our adversarial mask effectiveness in real-world experiments by printing the adversarial pattern on a fabric medical face mask, causing the FR system to identify only 3. 34% of the participants wearing the mask (compared to a minimum of 83. 34% with other evaluated masks).
DPC: Unsupervised Deep Point Correspondence via Cross and Self Construction
We present a new method for real-time non-rigid dense correspondence between point clouds based on structured shape construction.
Ranked #1 on
3D Dense Shape Correspondence
on SHREC'19
DeepBBS: Deep Best Buddies for Point Cloud Registration
The Best Buddies criterion is a strong indication for correct matches that, in turn, leads to accurate registration.
kNet: A Deep kNN Network To Handle Label Noise
To use kNet, we first train a preliminary network on the data set, and then train kNet on the penultimate layer of the preliminary network. We find that kNet gives a smooth approximation of kNN, and cannot handle the sharp label changes between samples that kNN can exhibit.
Reducing ReLU Count for Privacy-Preserving CNN Speedup
Experiments on several datasets reveal that we can cut the number of ReLU operations by up to three orders of magnitude and, as a result, cut the communication bandwidth by more than 50%.
Geometric Adversarial Attacks and Defenses on 3D Point Clouds
Additionally, we demonstrate the robustness of our attack in the case of defense, where we show that remnant characteristics of the target shape are still present at the output after applying the defense to the adversarial input.
Rethinking FUN: Frequency-Domain Utilization Networks
The search for efficient neural network architectures has gained much focus in recent years, where modern architectures focus not only on accuracy but also on inference time and model size.
Best Buddies Registration for Point Clouds
We propose new, and robust, loss functions for the point cloud registration problem.
Co-occurrence Based Texture Synthesis
As image generation techniques mature, there is a growing interest in explainable representations that are easy to understand and intuitive to manipulate.
Proximity Preserving Binary Code using Signed Graph-Cut
We show that the proposed approximation is superior to the commonly used spectral methods with respect to both accuracy and complexity.
Deep Image Compression using Decoder Side Information
We base our algorithm on the assumption that the image available to the encoder and the image available to the decoder are correlated, and we let the network learn these correlations in the training phase.
Graph Embedded Pose Clustering for Anomaly Detection
We propose a new method for anomaly detection of human actions.
SampleNet: Differentiable Point Cloud Sampling
As the size of the point cloud grows, so do the computational demands of these tasks.
3D Point Cloud Classification
3D Point Cloud Reconstruction
+1
Learn Stereo, Infer Mono: Siamese Networks for Self-Supervised, Monocular, Depth Estimation
The field of self-supervised monocular depth estimation has seen huge advancements in recent years.
Ranked #26 on
Monocular Depth Estimation
on KITTI Eigen split
CrowdCam: Dynamic Region Segmentation
We consider the problem of segmenting dynamic regions in CrowdCam images, where a dynamic region is the projection of a moving 3D object on the image plane.
Underwater Single Image Color Restoration Using Haze-Lines and a New Quantitative Dataset
The attenuation depends both on the water body and the 3D structure of the scene, making color restoration difficult.
Matching Pixels Using Co-Occurrence Statistics
We propose a new error measure for matching pixels that is based on co-occurrence statistics.
The Resistance to Label Noise in K-NN and DNN Depends on its Concentration
We investigate the classification performance of K-nearest neighbors (K-NN) and deep neural networks (DNNs) in the presence of label noise.
Co-occurrence Filter
It is based on the Bilateral Filter (BF) but instead of using a Gaussian on the range values to preserve edges it relies on a co-occurrence matrix.
Detecting Moving Regions in CrowdCam Images
We address the novel problem of detecting dynamic regions in CrowdCam images, a set of still images captured by a group of people.
Best-Buddies Tracking
BBS was introduced as a similarity measure between two point sets and was shown to be very effective for template matching.
Best-Buddies Similarity - Robust Template Matching using Mutual Nearest Neighbors
We propose a novel method for template matching in unconstrained environments.
Non-Local Image Dehazing
This dependency is expressed in the transmission coefficients, that control the scene attenuation and amount of haze in every pixel.
Peeking Template Matching for Depth Extension
We demonstrate on real-world data that our algorithm is capable of completing a full 3D scene from a single depth image and can synthesize a full depth map from a novel viewpoint of the scene.
Spatially Coherent Random Forests
Each tree in the forest produces a segmentation of the image plane and the boundaries of the segmentations of all trees are aggregated to produce a final hierarchical contour map.
Best-Buddies Similarity for Robust Template Matching
We propose a novel method for template matching in unconstrained environments.
Inverting RANSAC: Global Model Detection via Inlier Rate Estimation
This work presents a novel approach for detecting inliers in a given set of correspondences (matches).
Stereo on a budget
Instead of having both cameras send their entire image to the host computer, the left camera sends its image to the host while the right camera sends only a fraction $\epsilon$ of its image.
FasT-Match: Fast Affine Template Matching
Fast-Match is a fast algorithm for approximate template matching under 2D affine transformations that minimizes the Sum-of-Absolute-Differences (SAD) error measure.
