Papers RGB Salient Object Detection
“RGB Salient Object Detection” 태그가 달린 논문 222편 · 필터 해제
Patch-Depth Fusion: Dichotomous Image Segmentation via Fine-Grained Patch Strategy and Depth Integrity-Prior
Dichotomous Image Segmentation (DIS) is a high-precision object segmentation task for high-resolution natural images. The current mainstream methods focus on the optimization of local details but overlook the fundamental…
Dichotomous Image SegmentationImage SegmentationRGB Salient Object DetectionSegmentation+1CPDR: Towards Highly-Efficient Salient Object Detection via Crossed Post-decoder Refinement
Most of the current salient object detection approaches use deeper networks with large backbones to produce more accurate predictions, which results in a significant increase in computational complexity. A great number o…
Decoderobject-detectionObject DetectionRGB Salient Object Detection+1CoLA: Conditional Dropout and Language-driven Robust Dual-modal Salient Object Detection
The depth/thermal information is beneficial for detecting salient object with conventional RGB images. However, in dual-modal salient object detection (SOD) model, the robustness against noisy inputs and modality missing…
CoLALanguage ModelingLanguage Modellingobject-detection+5Bilateral Reference for High-Resolution Dichotomous Image Segmentation
We introduce a novel bilateral reference framework (BiRefNet) for high-resolution dichotomous image segmentation (DIS). It comprises two essential components: the localization module (LM) and the reconstruction module (R…
Camouflaged Object SegmentationDichotomous Image SegmentationImage SegmentationObject Localization+2M$^3$Net: Multilevel, Mixed and Multistage Attention Network for Salient Object Detection
Most existing salient object detection methods mostly use U-Net or feature pyramid structure, which simply aggregates feature maps of different scales, ignoring the uniqueness and interdependence of them and their respec…
object-detectionObject DetectionRGB Salient Object DetectionSalient Object DetectionRevisiting Image Pyramid Structure for High Resolution Salient Object Detection
Salient object detection (SOD) has been in the spotlight recently, yet has been studied less for high-resolution (HR) images. Unfortunately, HR images and their pixel-level annotations are certainly more labor-intensive …
Dichotomous Image SegmentationObject DetectionRGB Salient Object DetectionSalient Object Detection+1A Weakly Supervised Learning Framework for Salient Object Detection via Hybrid Labels
Fully-supervised salient object detection (SOD) methods have made great progress, but such methods often rely on a large number of pixel-level annotations, which are time-consuming and labour-intensive. In this paper, we…
object-detectionObject DetectionRGB Salient Object DetectionSaliency Detection+2Pyramid Grafting Network for One-Stage High Resolution Saliency Detection
Recent salient object detection (SOD) methods based on deep neural network have achieved remarkable performance. However, most of existing SOD models designed for low-resolution input perform poorly on high-resolution im…
4k8kobject-detectionObject Detection+4TRACER: Extreme Attention Guided Salient Object Tracing Network
Existing studies on salient object detection (SOD) focus on extracting distinct objects with edge information and aggregating multi-level features to improve SOD performance. To achieve satisfactory performance, the meth…
Computational EfficiencyDecoderObjectobject-detection+3C$^{4}$Net: Contextual Compression and Complementary Combination Network for Salient Object Detection
Deep learning solutions of the salient object detection problem have achieved great results in recent years. The majority of these models are based on encoders and decoders, with a different multi-feature combination. In…
object-detectionObject DetectionRGB Salient Object DetectionSaliency Detection+1Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss
UNet-based methods have shown outstanding performance in salient object detection (SOD), but are problematic in two aspects. 1) Indiscriminately integrating the encoder feature, which contains spatial information for mul…
DecoderObjectobject-detectionObject Detection+3Disentangled High Quality Salient Object Detection
Aiming at discovering and locating most distinctive objects from visual scenes, salient object detection (SOD) plays an essential role in various computer vision systems. Coming to the era of high resolution, SOD methods…
GPUObjectobject-detectionObject Detection+4P2T: Pyramid Pooling Transformer for Scene Understanding
Recently, the vision transformer has achieved great success by pushing the state-of-the-art of various vision tasks. One of the most challenging problems in the vision transformer is that the large sequence length of ima…
image-classificationImage ClassificationInstance Segmentationobject-detection+5Densely Deformable Efficient Salient Object Detection Network
Salient Object Detection (SOD) domain using RGB-D data has lately emerged with some current models' adequately precise results. However, they have restrained generalization abilities and intensive computational complexit…
Objectobject-detectionRGB-D Salient Object DetectionRGB Salient Object Detection+2Uncertainty Inspired RGB-D Saliency Detection
We propose the first stochastic framework to employ uncertainty for RGB-D saliency detection by learning from the data labeling process. Existing RGB-D saliency detection models treat this task as a point estimation prob…
DecoderRGB-D Salient Object DetectionRGB Salient Object DetectionSaliency Detection+1Regularized Densely-connected Pyramid Network for Salient Instance Segmentation
Much of the recent efforts on salient object detection (SOD) have been devoted to producing accurate saliency maps without being aware of their instance labels. To this end, we propose a new pipeline for end-to-end salie…
DecoderInstance Segmentationobject-detectionObject Detection+3Siamese Network for RGB-D Salient Object Detection and Beyond
Existing RGB-D salient object detection (SOD) models usually treat RGB and depth as independent information and design separate networks for feature extraction from each. Such schemes can easily be constrained by a limit…
object-detectionObject DetectionRGB-D Salient Object DetectionRGB Salient Object Detection+2Label Decoupling Framework for Salient Object Detection
To get more accurate saliency maps, recent methods mainly focus on aggregating multi-level features from fully convolutional network (FCN) and introducing edge information as auxiliary supervision. Though remarkable prog…
Objectobject-detectionObject DetectionRGB Salient Object Detection+2Progressively Guided Alternate Refinement Network for RGB-D Salient Object Detection
In this paper, we aim to develop an efficient and compact deep network for RGB-D salient object detection, where the depth image provides complementary information to boost performance in complex scenarios. Starting from…
object-detectionObject DetectionRGB-D Salient Object DetectionRGB Salient Object Detection+1DyStaB: Unsupervised Object Segmentation via Dynamic-Static Bootstrapping
We describe an unsupervised method to detect and segment portions of images of live scenes that, at some point in time, are seen moving as a coherent whole, which we refer to as objects. Our method first partitions the m…
Continual LearningObjectobject-detectionObject Detection+7