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RGB-D Salient Object Detection

30 papers with code · Computer Vision
Subtask of Object Detection

RGB-D Salient object detection (SOD) aims at distinguishing the most visually distinctive objects or regions in a scene from the given RGB and Depth data. It has a wide range of applications, including video/image segmentation, object recognition, visual tracking, foreground maps evaluation, image retrieval, content-aware image editing, information discovery, photosynthesis, and weakly supervised semantic segmentation. Here, depth information plays an important complementary role in finding salient objects. Online benchmark: http://dpfan.net/d3netbenchmark.

( Image credit: Rethinking RGB-D Salient Object Detection: Models, Data Sets, and Large-Scale Benchmarks, TNNLS20 )

Benchmarks

Greatest papers with code

Uncertainty Inspired RGB-D Saliency Detection

7 Sep 2020JingZhang617/UCNet

Our framework includes two main models: 1) a generator model, which maps the input image and latent variable to stochastic saliency prediction, and 2) an inference model, which gradually updates the latent variable by sampling it from the true or approximate posterior distribution.

RGB-D SALIENT OBJECT DETECTION RGB SALIENT OBJECT DETECTION SALIENCY PREDICTION

UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders

CVPR 2020 JingZhang617/UCNet

In this paper, we propose the first framework (UCNet) to employ uncertainty for RGB-D saliency detection by learning from the data labeling process.

RGB-D SALIENT OBJECT DETECTION SALIENCY DETECTION

Depth-Induced Multi-Scale Recurrent Attention Network for Saliency Detection

ICCV 2019 jiwei0921/DMRA

In this work, we propose a novel depth-induced multi-scale recurrent attention network for saliency detection.

Ranked #11 on RGB-D Salient Object Detection on NJU2K (using extra training data)

RGB-D SALIENT OBJECT DETECTION SALIENCY DETECTION SCENE UNDERSTANDING

RGB-D Salient Object Detection: A Survey

1 Aug 2020DengPingFan/D3NetBenchmark

Further, considering that the light field can also provide depth maps, we review SOD models and popular benchmark datasets from this domain as well.

RGB-D SALIENT OBJECT DETECTION RGB SALIENT OBJECT DETECTION

Siamese Network for RGB-D Salient Object Detection and Beyond

26 Aug 2020kerenfu/JLDCF

Inspired by the observation that RGB and depth modalities actually present certain commonality in distinguishing salient objects, a novel joint learning and densely cooperative fusion (JL-DCF) architecture is designed to learn from both RGB and depth inputs through a shared network backbone, known as the Siamese architecture.

 Ranked #1 on RGB-D Salient Object Detection on SIP (using extra training data)

RGB-D SALIENT OBJECT DETECTION VIDEO SALIENT OBJECT DETECTION

Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection

CVPR 2019 taozh2017/RGBD-SODsurvey

The large availability of depth sensors provides valuable complementary information for salient object detection (SOD) in RGBD images.

RGB-D SALIENT OBJECT DETECTION RGB SALIENT OBJECT DETECTION

Adaptive Fusion for RGB-D Salient Object Detection

5 Jan 2019Lucia-Ningning/Adaptive_Fusion_RGBD_Saliency_Detection

RGB-D salient object detection aims to identify the most visually distinctive objects in a pair of color and depth images.

RGB-D SALIENT OBJECT DETECTION RGB SALIENT OBJECT DETECTION

Hierarchical Dynamic Filtering Network for RGB-D Salient Object Detection

ECCV 2020 lartpang/HDFNet

The main purpose of RGB-D salient object detection (SOD) is how to better integrate and utilize cross-modal fusion information.

RGB-D SALIENT OBJECT DETECTION RGB SALIENT OBJECT DETECTION