Towards Accurate RGB-D Saliency Detection with Complementary Attention and Adaptive Integration

by   Hong-Bo Bi, et al.

Saliency detection based on the complementary information from RGB images and depth maps has recently gained great popularity. In this paper, we propose Complementary Attention and Adaptive Integration Network (CAAI-Net), a novel RGB-D saliency detection model that integrates complementary attention based feature concentration and adaptive cross-modal feature fusion into a unified framework for accurate saliency detection. Specifically, we propose a context-aware complementary attention (CCA) module, which consists of a feature interaction component, a complementary attention component, and a global-context component. The CCA module first utilizes the feature interaction component to extract rich local context features. The resulting features are then fed into the complementary attention component, which employs the complementary attention generated from adjacent levels to guide the attention at the current layer so that the mutual background disturbances are suppressed and the network focuses more on the areas with salient objects. Finally, we utilize a specially-designed adaptive feature integration (AFI) module, which sufficiently considers the low-quality issue of depth maps, to aggregate the RGB and depth features in an adaptive manner. Extensive experiments on six challenging benchmark datasets demonstrate that CAAI-Net is an effective saliency detection model and outperforms nine state-of-the-art models in terms of four widely-used metrics. In addition, extensive ablation studies confirm the effectiveness of the proposed CCA and AFI modules.


page 1

page 3

page 4

page 5

page 6

page 7

page 11

page 12


Specificity-preserving RGB-D Saliency Detection

RGB-D saliency detection has attracted increasing attention, due to its ...

RGB-D Salient Object Detection with Cross-Modality Modulation and Selection

We present an effective method to progressively integrate and refine the...

Context-aware Cross-level Fusion Network for Camouflaged Object Detection

Camouflaged object detection (COD) is a challenging task due to the low ...

Transformer-based Network for RGB-D Saliency Detection

RGB-D saliency detection integrates information from both RGB images and...

CT-Net: Complementary Transfering Network for Garment Transfer with Arbitrary Geometric Changes

Garment transfer shows great potential in realistic applications with th...

Depth-aware Glass Surface Detection with Cross-modal Context Mining

Glass surfaces are becoming increasingly ubiquitous as modern buildings ...

An Unsupervised Game-Theoretic Approach to Saliency Detection

We propose a novel unsupervised game-theoretic salient object detection ...

Please sign up or login with your details

Forgot password? Click here to reset