Search Results for author:
Found 14 papers, 5 papers with code
Optimizing Fiducial Marker Placement for Improved Visual Localization
Our main contribution is a novel framework for modeling camera localizability that incorporates both natural scene features and artificial fiducial markers added to the scene.
PatchMatch-Based Neighborhood Consensus for Semantic Correspondence
We address estimating dense correspondences between two images depicting different but semantically related scenes.
Efficient Scene Compression for Visual-based Localization
Estimating the pose of a camera with respect to a 3D reconstruction or scene representation is a crucial step for many mixed reality and robotics applications.
Generalized Pose-and-Scale Estimation using 4-Point Congruence Constraints
We present gP4Pc, a new method for computing the absolute pose of a generalized camera with unknown internal scale from four corresponding 3D point-and-ray pairs.
BLT: Balancing Long-Tailed Datasets with Adversarially-Perturbed Images
Unfortunately, this imbalance enables a visual recognition system to perform well on head classes but poorly on tail classes.
Ranked #52 on
Long-tail Learning
on ImageNet-LT
HyperSTAR: Task-Aware Hyperparameters for Deep Networks
To reduce HPO time, we present HyperSTAR (System for Task Aware Hyperparameter Recommendation), a task-aware method to warm-start HPO for deep neural networks.
gDLS*: Generalized Pose-and-Scale Estimation Given Scale and Gravity Priors
Many real-world applications in augmented reality (AR), 3D mapping, and robotics require both fast and accurate estimation of camera poses and scales from multiple images captured by multiple cameras or a single moving camera.
Patch Correspondences for Interpreting Pixel-level CNNs
We present compositional nearest neighbors (CompNN), a simple approach to visually interpreting distributed representations learned by a convolutional neural network (CNN) for pixel-level tasks (e. g., image synthesis and segmentation).
GraphMatch: Efficient Large-Scale Graph Construction for Structure from Motion
We present GraphMatch, an approximate yet efficient method for building the matching graph for large-scale structure-from-motion (SfM) pipelines.
ANSAC: Adaptive Non-minimal Sample and Consensus
While RANSAC-based methods are robust to incorrect image correspondences (outliers), their hypothesis generators are not robust to correct image correspondences (inliers) with positional error (noise).
One-Class Slab Support Vector Machine
This work introduces the one-class slab SVM (OCSSVM), a one-class classifier that aims at improving the performance of the one-class SVM.
Large Scale SfM with the Distributed Camera Model
We introduce the distributed camera model, a novel model for Structure-from-Motion (SfM).
Eye-CU: Sleep Pose Classification for Healthcare using Multimodal Multiview Data
This work addresses these issues by introducing a new method and a new system for robust automated classification of sleep poses in an Intensive Care Unit (ICU) environment.
SWIGS: A Swift Guided Sampling Method
We present SWIGS, a Swift and efficient Guided Sampling method for robust model estimation from image feature correspondences.
