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Found 13 papers, 7 papers with code
A Multi-In-Single-Out Network for Video Frame Interpolation without Optical Flow
In general, deep learning-based video frame interpolation (VFI) methods have predominantly focused on estimating motion vectors between two input frames and warping them to the target time.
1st Place Solution to MultiEarth 2023 Challenge on Multimodal SAR-to-EO Image Translation
The Multimodal Learning for Earth and Environment Workshop (MultiEarth 2023) aims to harness the substantial amount of remote sensing data gathered over extensive periods for the monitoring and analysis of Earth's ecosystems'health.
VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sorting
To test the abilities of computer vision models on this task, we present the VisDA 2022 Challenge on Domain Adaptation for Industrial Waste Sorting.
CAFS: Class Adaptive Framework for Semi-Supervised Semantic Segmentation
Unlike existing semi-supervised semantic segmentation frameworks, CAFS constructs a validation set on a labeled dataset, to leverage the calibration performance for each class.
Bidirectional Domain Mixup for Domain Adaptive Semantic Segmentation
In specific, we achieve domain mixup in two-step: cut and paste.
1st Place Solution to NeurIPS 2022 Challenge on Visual Domain Adaptation
The Visual Domain Adaptation(VisDA) 2022 Challenge calls for an unsupervised domain adaptive model in semantic segmentation tasks for industrial waste sorting.
Source Domain Subset Sampling for Semi-Supervised Domain Adaptation in Semantic Segmentation
In this paper, we introduce source domain subset sampling (SDSS) as a new perspective of semi-supervised domain adaptation.
Unsupervised Change Detection Based on Image Reconstruction Loss
In this paper, we propose unsupervised change detection based on image reconstruction loss using only unlabeled single temporal single image.
PT4AL: Using Self-Supervised Pretext Tasks for Active Learning
Before the active learning iterations, the pretext task learner is trained on the unlabeled set, and the unlabeled data are sorted and split into batches by their pretext task losses.
Ranked #2 on
Active Learning
on CIFAR10 (10,000)
Exploiting Features with Split-and-Share Module
Deep convolutional neural networks (CNNs) have shown state-of-the-art performances in various computer vision tasks.
Sequential Feature Filtering Classifier
We propose Sequential Feature Filtering Classifier (FFC), a simple but effective classifier for convolutional neural networks (CNNs).
Gradient-based Camera Exposure Control for Outdoor Mobile Platforms
We introduce a novel method to automatically adjust camera exposure for image processing and computer vision applications on mobile robot platforms.
Vision System and Depth Processing for DRC-HUBO+
This paper presents a vision system and a depth processing algorithm for DRC-HUBO+, the winner of the DRC finals 2015.
