Search Results for author:
Found 16 papers, 6 papers with code
MVPatch: More Vivid Patch for Adversarial Camouflaged Attacks on Object Detectors in the Physical World
Our method employs a model-perception-based approach that reduces the object confidence scores of several object detectors to boost the transferability of adversarial patches.
OV-VG: A Benchmark for Open-Vocabulary Visual Grounding
While current foundational models excel at various visual language tasks, there's a noticeable absence of models specifically tailored for open-vocabulary visual grounding.
Iterative Robust Visual Grounding with Masked Reference based Centerpoint Supervision
The proposed framework is evaluated on five regular VG datasets and two newly constructed robust VG datasets.
Change Detection Methods for Remote Sensing in the Last Decade: A Comprehensive Review
We first introduce some preliminary knowledge for the change detection task, such as problem definition, datasets, evaluation metrics, and transformer basics, as well as provide a detailed taxonomy of existing algorithms from three different perspectives: algorithm granularity, supervision modes, and learning frameworks in the methodology section.
Local-to-Global Information Communication for Real-Time Semantic Segmentation Network Search
For local information exchange, a graph convolutional network (GCN) guided module is seamlessly integrated as a communication deliver between cells.
Self-Training Guided Disentangled Adaptation for Cross-Domain Remote Sensing Image Semantic Segmentation
We first propose source student backbone and target student backbone to respectively extract the source-style and target-style feature for both source and target images.
Look in Different Views: Multi-Scheme Regression Guided Cell Instance Segmentation
On the DSB2018 and CA2. 5, our network surpasses previous methods by 1. 2% (AP50).
MMOTU: A Multi-Modality Ovarian Tumor Ultrasound Image Dataset for Unsupervised Cross-Domain Semantic Segmentation
To solve this problem, we propose a Multi-Modality Ovarian Tumor Ultrasound (MMOTU) image dataset containing 1469 2d ultrasound images and 170 contrast enhanced ultrasonography (CEUS) images with pixel-wise and global-wise annotations.
Attention-based Feature Decomposition-Reconstruction Network for Scene Text Detection
In this paper, we propose attention-based feature decomposition-reconstruction network for scene text detection, which utilizes contextual information and low-level feature to enhance the performance of segmentation-based text detector.
A Feature Consistency Driven Attention Erasing Network for Fine-Grained Image Retrieval
To handle these two issues, we propose a feature consistency driven attention erasing network (FCAENet) for fine-grained image retrieval.
TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-captured Scenarios
Object detection on drone-captured scenarios is a recent popular task.
A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation
To deal with the above two issues, we propose self-distillation embedded supervised affinity attention model to improve the performance of few-shot segmentation task.
Embedded Self-Distillation in Compact Multi-Branch Ensemble Network for Remote Sensing Scene Classification
On this issue, we embed self-distillation (SD) method to transfer knowledge from ensemble network to main-branch in it.
Embedded Knowledge Distillation in Depth-Level Dynamic Neural Network
In real applications, different computation-resource devices need different-depth networks (e. g., ResNet-18/34/50) with high-accuracy.
MM-FSOD: Meta and metric integrated few-shot object detection
In this paper, we present an effective object detection framework (MM-FSOD) that integrates metric learning and meta-learning to tackle the few-shot object detection task.
MGML: Multi-Granularity Multi-Level Feature Ensemble Network for Remote Sensing Scene Classification
To avoid the interference from confusing information, we propose Multi-granularity Multi-Level Feature Ensemble Module (MGML-FEM) which can provide diverse predictions by full-channel feature generator (FC-FG).
