In this paper, we aim to design an efficient real-time object detector that exceeds the YOLO
series and is easily extensible for many object recognition tasks such as instance …

Visual segmentation seeks to partition images, video frames, or point clouds into multiple
segments or groups. This technique has numerous real-world applications, such as …

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 …

Image segmentation is the task of associating pixels in an image with their respective object
class labels. It has a wide range of applications in many industries including healthcare …

Most existing methods realize 3D instance segmentation by extending those models used
for 3D object detection or 3D semantic segmentation. However, these non-straightforward …

We present CLUSTSEG, a general, transformer-based framework that tackles different
image segmentation tasks (ie, superpixel, semantic, instance, and panoptic) through a …

In this paper, we propose YOSO, a real-time panoptic segmentation framework. YOSO
predicts masks via dynamic convolutions between panoptic kernels and image feature …

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 …

Recent attention in instance segmentation has focused on query-based models. Despite
being non-maximum suppression (NMS)-free and end-to-end, the superiority of these …

Abstract 3D lane detection from monocular images is a fundamental yet challenging task in
autonomous driving. Recent advances primarily rely on structural 3D surrogates (eg, bird's …