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Found 10 papers, 5 papers with code
Bag of Tricks for Domain Adaptive Multi-Object Tracking
To maximize the performance on real data, we first propose to use pseudo-labeling that generates imperfect labels for real data using a model trained with synthetic dataset.
Learning Multiple Probabilistic Degradation Generators for Unsupervised Real World Image Super Resolution
Although the goal of training the degradation generator is to approximate the distribution of LR images given a HR image, previous works have heavily relied on the unrealistic assumption that the conditional distribution is a delta function and learned the deterministic mapping from the HR image to a LR image.
An End-to-End Trainable Video Panoptic Segmentation Method usingTransformers
In this paper, we present an algorithm to tackle a video panoptic segmentation problem, a newly emerging area of research.
Simple and Efficient Unpaired Real-world Super-Resolution using Image Statistics
However, it is not easy to stably learn such a translation with GANs using unpaired data.
Online Multi-Object Tracking and Segmentation with GMPHD Filter and Mask-based Affinity Fusion
One affinity, for position and motion, is computed by using the GMPHD filter, and the other affinity, for appearance is computed by using the responses from a single object tracker such as a kernalized correlation filter.
NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results
This paper reviews the NTIRE 2020 challenge on perceptual extreme super-resolution with focus on proposed solutions and results.
Online Multi-Object Tracking Framework with the GMPHD Filter and Occlusion Group Management
In this paper, we propose an efficient online multi-object tracking framework based on the GMPHD filter and occlusion group management scheme where the GMPHD filter utilizes hierarchical data association to reduce the false negatives caused by miss detection.
Ranked #1 on
Online Multi-Object Tracking
on MOT15
Online Multiple Pedestrians Tracking using Deep Temporal Appearance Matching Association
The higher dimension of inherent information in the appearance model compared to the geometric model is problematic in many ways.
Multiple Hypothesis Tracking Algorithm for Multi-Target Multi-Camera Tracking with Disjoint Views
Furthermore, multi-target tracking within a camera is performed simultaneously with the tree formation by manipulating a status of each track hypothesis.
Online Multi-Object Tracking with Historical Appearance Matching and Scene Adaptive Detection Filtering
In this paper, we propose the methods to handle temporal errors during multi-object tracking.
