Image instance segmentation involves labeling pixels of images with classes and instances,
which is one of the pivotal technologies in many domains, such as natural scenes …

Plant phenotype plays an important role in genetics, botany, and agronomy, while the
currently popular methods for phenotypic trait measurement have some limitations in …

Transformer, an attention-based encoder–decoder model, has already revolutionized the
field of natural language processing (NLP). Inspired by such significant achievements, some …

This paper presents ClusterFormer, a universal vision model that is based on the Clustering
paradigm with TransFormer. It comprises two novel designs: 1) recurrent cross-attention …

Video instance segmentation (VIS) is the task that requires simultaneously classifying,
segmenting and tracking object instances of interest in video. Recent methods typically …

Leveraging the extensive training data from SA-1B, the segment anything model (SAM)
demonstrates remarkable generalization and zero-shot capabilities. However, as a category …

We present QueryInst, a new perspective for instance segmentation. QueryInst is a multi-
stage end-to-end system that treats instances of interest as learnable queries, enabling …

Deep learning-based object detection and instance segmentation have achieved
unprecedented progress. In this article, we propose complete-IoU (CIoU) loss and Cluster …

In this work, we design a simple, direct, and fast framework for instance segmentation with
strong performance. To this end, we propose a novel and effective approach, termed …

Prevalent state-of-the-art instance segmentation methods fall into a query-based scheme, in
which instance masks are derived by querying the image feature using a set of instance …