In recent years a vast amount of visual content has been generated and shared from many
fields, such as social media platforms, medical imaging, and robotics. This abundance of …

In the early days, content-based image retrieval (CBIR) was studied with global features.
Since 2003, image retrieval based on local descriptors (de facto SIFT) has been extensively …

Aiming at the problems of high missed detection rates of the YOLOv7 algorithm for vehicle
detection on urban roads, weak perception of small targets in perspective, and insufficient …

We propose a simple, fast, and accurate one-stage approach to visual grounding, inspired
by the following insight. The performances of existing propose-and-rank two-stage methods …

Abstract 3D visual grounding aims at grounding a natural language description about a 3D
scene, usually represented in the form of 3D point clouds, to the targeted object region. Point …

Abstract Referring Expression Comprehension (REC) aims to localize the target objects
specified by free-form natural language descriptions in images. While state-of-the-art …

Abstract 3D visual grounding task has been explored with visual and language streams to
comprehend referential language for identifying targeted objects in 3D scenes. However …

Faster R-CNN (R corresponds to “Region”) which combined the RPN network and the Fast
R-CNN network is one of the best ways to object detection of R-CNN series based on deep …

Computer vision (CV) and human–computer interaction (HCI) are essential in many
technological fields. Researchers in CV are particularly interested in real-time object …

We tackle the problem of one-shot instance segmentation: Given an example image of a
novel, previously unknown object category, find and segment all objects of this category …