Segmenting polyps from colonoscopy images is very important in clinical practice since it
provides valuable information for colorectal cancer. However, polyp segmentation remains a …

Depth images and thermal images contain the spatial geometry information and surface
temperature information, which can act as complementary information for the RGB modality …

Multi-modal salient object detection (MSOD) aims to boost saliency detection performance
by integrating visible sources with depth or thermal infrared ones. Existing methods …

Vision-based measurement techniques are required in the quality inspection process of
various products. However, most of the existing research methods focus on the use of a …

Previous multi-task dense prediction studies developed complex pipelines such as multi-
modal distillations in multiple stages or searching for task relational contexts for each task …

RGB-Thermal salient object detection (SOD) aims to merge two spectral images to segment
visually appealing objects. Current methods primarily extract salient object information in the …

In this paper, we present a weakly-supervised RGB-D salient object detection model via
scribble supervision. Specifically, as a multimodal learning task, we focus on effective …

While significant progress has been made in recent years in the field of salient object
detection, there are still limitations in heterogeneous modality fusion and salient feature …

RGB-D salient object detection (SOD) has gained tremendous attention in recent years. In
particular, transformer has been employed and shown great potential. However, existing …

Abstract Image Salient Object Detection (SOD) is a fundamental research topic in the area of
computer vision. Recently, the multimodal information in RGB, Depth (D), and Thermal (T) …