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Found 23 papers, 6 papers with code
Multiplex Anti-Asian Sentiment before and during the Pandemic: Introducing New Datasets from Twitter Mining
We introduce new datasets from Twitter related to anti-Asian hate sentiment before and during the pandemic.
Bridging Data Islands: Geographic Heterogeneity-Aware Federated Learning for Collaborative Remote Sensing Semantic Segmentation
Remote sensing semantic segmentation (RSS) is an essential task in Earth Observation missions.
AUG: A New Dataset and An Efficient Model for Aerial Image Urban Scene Graph Generation
To fill in the gap of the overhead view dataset, this paper constructs and releases an aerial image urban scene graph generation (AUG) dataset.
MoCha-Stereo: Motif Channel Attention Network for Stereo Matching
In addition, edge variations in %potential feature channels of the reconstruction error map also affect details matching, we propose the Reconstruction Error Motif Penalty (REMP) module to further refine the full-resolution disparity estimation.
Ranked #1 on
Stereo Depth Estimation
on KITTI 2015
SpirDet: Towards Efficient, Accurate and Lightweight Infrared Small Target Detector
To tackle this challenge, we propose SpirDet, a novel approach for efficient detection of infrared small targets.
AllSpark: A Multimodal Spatio-Temporal General Intelligence Model with Thirteen Modalities
We introduce the Language as Reference Framework (LaRF), a fundamental principle for constructing a multimodal unified model, aiming to strike a trade-off between the cohesion and autonomy among different modalities.
SkySense: A Multi-Modal Remote Sensing Foundation Model Towards Universal Interpretation for Earth Observation Imagery
Prior studies on Remote Sensing Foundation Model (RSFM) reveal immense potential towards a generic model for Earth Observation.
Learning to Holistically Detect Bridges from Large-Size VHR Remote Sensing Imagery
Therefore, to ensure the visibility and integrity of bridges, it is essential to perform holistic bridge detection in large-size very-high-resolution (VHR) RSIs.
LLVMs4Protest: Harnessing the Power of Large Language and Vision Models for Deciphering Protests in the News
First, the longformer model was fine-tuned using the Dynamic of Collective Action (DoCA) Corpus.
Imbalance Knowledge-Driven Multi-modal Network for Land-Cover Semantic Segmentation Using Images and LiDAR Point Clouds
The present multi-modal methods usually map high-dimensional features to low-dimensional spaces as a preprocess before feature extraction to address the nonnegligible domain gap, which inevitably leads to information loss.
GLH-Water: A Large-Scale Dataset for Global Surface Water Detection in Large-Size Very-High-Resolution Satellite Imagery
Global surface water detection in very-high-resolution (VHR) satellite imagery can directly serve major applications such as refined flood mapping and water resource assessment.
RIFT2: Speeding-up RIFT with A New Rotation-Invariance Technique
Multimodal image matching is an important prerequisite for multisource image information fusion.
High-Frequency Stereo Matching Network
In the field of binocular stereo matching, remarkable progress has been made by iterative methods like RAFT-Stereo and CREStereo.
Progressive Learning with Cross-Window Consistency for Semi-Supervised Semantic Segmentation
Semi-supervised semantic segmentation focuses on the exploration of a small amount of labeled data and a large amount of unlabeled data, which is more in line with the demands of real-world image understanding applications.
EHSNet: End-to-End Holistic Learning Network for Large-Size Remote Sensing Image Semantic Segmentation
This paper presents EHSNet, a new end-to-end segmentation network designed for the holistic learning of large-size remote sensing image semantic segmentation (LRISS).
Hierarchical Memory Learning for Fine-Grained Scene Graph Generation
After the autonomous partition of coarse and fine predicates, the model is first trained on the coarse predicates and then learns the fine predicates.
LiDAR-guided Stereo Matching with a Spatial Consistency Constraint
Next, we propose a riverbed enhancement function to optimize the cost volume of the LiDAR projection points and their homogeneous pixels to improve the matching robustness.
Asymmetric Hash Code Learning for Remote Sensing Image Retrieval
In this paper, we propose a novel deep hashing method, named asymmetric hash code learning (AHCL), for RSIR.
ELSR: Efficient Line Segment Reconstruction With Planes and Points Guidance
In this paper, we propose an efficient line segment reconstruction method called ELSR.
RMNA: A Neighbor Aggregation-Based Knowledge Graph Representation Learning Model Using Rule Mining
Therefore, neighbor aggregation-based representation learning (NARL) models are proposed, which encode the information in the neighbors of an entity into its embeddings.
Group-Aware Graph Neural Network for Nationwide City Air Quality Forecasting
The model constructs a city graph and a city group graph to model the spatial and latent dependencies between cities, respectively.
Collaboratively boosting data-driven deep learning and knowledge-guided ontological reasoning for semantic segmentation of remote sensing imagery
As one kind of architecture from the deep learning family, deep semantic segmentation network (DSSN) achieves a certain degree of success on the semantic segmentation task and obviously outperforms the traditional methods based on hand-crafted features.
Segmentation Of Remote Sensing Imagery
Semantic Segmentation
FA-Harris: A Fast and Asynchronous Corner Detector for Event Cameras
The proposed G-SAE maintenance algorithm and corner candidate selection algorithm greatly enhance the real-time performance for corner detection, while the corner candidate refinement algorithm maintains the accuracy of performance by using an improved event-based Harris detector.
