Detecting and segmenting salient objects from natural scenes, often referred to as salient
object detection, has attracted great interest in computer vision. While many models have …

This tutorial reviews image alignment and image stitching algorithms. Image alignment
algorithms can discover the correspondence relationships among images with varying …

In this work, we present SEEM, a promotable and interactive model for segmenting
everything everywhere all at once in an image. In SEEM, we propose a novel and versatile …

In this work, we introduce Semantic-SAM, an augmented image segmentation foundation for
segmenting and recognizing anything at desired granularities. Compared to the …

Interactive segmentation allows users to extract target masks by making positive/negative
clicks. Although explored by many previous works, there is still a gap between academic …

A neural radiance field (NeRF) is a scene model supporting high-quality view synthesis,
optimized per scene. In this paper, we explore enabling user editing of a category-level …

We present Modular interactive VOS (MiVOS) framework which decouples interaction-to-
mask and mask propagation, allowing for higher generalizability and better performance …

Large-scale data are of crucial importance for learning semantic segmentation models, but
annotating per-pixel masks is a tedious and inefficient procedure. We note that for the topic …

Most recent semantic segmentation methods train deep convolutional neural networks with
fully annotated masks requiring pixel-accuracy for good quality training. Common weakly …

Deep neural networks have become a mainstream approach to interactive segmentation. As
we show in our experiments, while for some images a trained network provides accurate …