Search Results for author:
Found 8 papers, 5 papers with code
Learning High-Resolution Domain-Specific Representations with a GAN Generator
Based on this finding, we propose LayerMatch scheme for approximating the representation of a GAN generator that can be used for unsupervised domain-specific pretraining.
Semi-Supervised Semantic Segmentation
Vocal Bursts Intensity Prediction
IterDet: Iterative Scheme for Object Detection in Crowded Environments
Deep learning-based detectors usually produce a redundant set of object bounding boxes including many duplicate detections of the same object.
Ranked #1 on
Object Detection
on WiderPerson
f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation
We propose f-BRS (feature backpropagating refinement scheme) that solves an optimization problem with respect to auxiliary variables instead of the network inputs, and requires running forward and backward pass just for a small part of a network.
Ranked #8 on
Interactive Segmentation
on SBD
Training Deep SLAM on Single Frames
We train visual odometry model on synthetic data and do not use ground truth poses hence this model can be considered unsupervised.
Measuring robustness of Visual SLAM
We find that while in many cases the accuracy of SLAM is very good, the robustness is still an issue.
DISCOMAN: Dataset of Indoor SCenes for Odometry, Mapping And Navigation
We present a novel dataset for training and benchmarking semantic SLAM methods.
AdaptIS: Adaptive Instance Selection Network
Given an input image and a point $(x, y)$, it generates a mask for the object located at $(x, y)$.
Ranked #9 on
Panoptic Segmentation
on Mapillary val
Scene Motion Decomposition for Learnable Visual Odometry
Optical Flow (OF) and depth are commonly used for visual odometry since they provide sufficient information about camera ego-motion in a rigid scene.
