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Found 9 papers, 5 papers with code
DDF: A Novel Dual-Domain Image Fusion Strategy for Remote Sensing Image Semantic Segmentation with Unsupervised Domain Adaptation
Semantic segmentation of remote sensing images is a challenging and hot issue due to the large amount of unlabeled data.
CrossDiff: Exploring Self-Supervised Representation of Pansharpening via Cross-Predictive Diffusion Model
Fusion of a panchromatic (PAN) image and corresponding multispectral (MS) image is also known as pansharpening, which aims to combine abundant spatial details of PAN and spectral information of MS. Due to the absence of high-resolution MS images, available deep-learning-based methods usually follow the paradigm of training at reduced resolution and testing at both reduced and full resolution.
Ground-to-Aerial Person Search: Benchmark Dataset and Approach
In this work, we construct a large-scale dataset for Ground-to-Aerial Person Search, named G2APS, which contains 31, 770 images of 260, 559 annotated bounding boxes for 2, 644 identities appearing in both of the UAVs and ground surveillance cameras.
Pre-train, Adapt and Detect: Multi-Task Adapter Tuning for Camouflaged Object Detection
Camouflaged object detection (COD), aiming to segment camouflaged objects which exhibit similar patterns with the background, is a challenging task.
MS-DETR: Multispectral Pedestrian Detection Transformer with Loosely Coupled Fusion and Modality-Balanced Optimization
Most of the available multispectral pedestrian detectors are based on non-end-to-end detectors, while in this paper, we propose MultiSpectral pedestrian DEtection TRansformer (MS-DETR), an end-to-end multispectral pedestrian detector, which extends DETR into the field of multi-modal detection.
Dual Modality Prompt Tuning for Vision-Language Pre-Trained Model
To make the final image feature concentrate more on the target visual concept, a Class-Aware Visual Prompt Tuning (CAVPT) scheme is further proposed in our DPT, where the class-aware visual prompt is generated dynamically by performing the cross attention between text prompts features and image patch token embeddings to encode both the downstream task-related information and visual instance information.
PC-GANs: Progressive Compensation Generative Adversarial Networks for Pan-sharpening
Most of the available deep learning-based pan-sharpening methods sharpen the multispectral images through a one-step scheme, which strongly depends on the reconstruction ability of the network.
Pansharpening via Frequency-Aware Fusion Network with Explicit Similarity Constraints
The process of fusing a high spatial resolution (HR) panchromatic (PAN) image and a low spatial resolution (LR) multispectral (MS) image to obtain an HRMS image is known as pansharpening.
Text-based Person Search in Full Images via Semantic-Driven Proposal Generation
Finding target persons in full scene images with a query of text description has important practical applications in intelligent video surveillance. However, different from the real-world scenarios where the bounding boxes are not available, existing text-based person retrieval methods mainly focus on the cross modal matching between the query text descriptions and the gallery of cropped pedestrian images.
