In the field of visual scene understanding, deep neural networks have made impressive
advancements in various core tasks like segmentation, tracking, and detection. However …

As the most fundamental scene understanding tasks, object detection and segmentation
have made tremendous progress in deep learning era. Due to the expensive manual …

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 …

We introduce Open3DIS a novel solution designed to tackle the problem of Open-
Vocabulary Instance Segmentation within 3D scenes. Objects within 3D environments …

We propose MAMo, a novel memory and attention framework for monocular video depth
estimation. MAMo can augment and improve any single-image depth estimation networks …

Open-vocabulary 3D instance segmentation is cutting-edge for its ability to segment 3D
instances without predefined categories. However progress in 3D lags behind its 2D …

This paper addresses the challenging problem of open-vocabulary object detection (OVOD)
where an object detector must identify both seen and unseen classes in test images without …

Few-Shot Instance Segmentation (FSIS) requires detecting and segmenting novel classes
with limited support examples. Existing methods based on Region Proposal Networks …

Active Learning (AL) aims to enhance the performance of deep models by selecting the most
informative samples for annotation from a pool of unlabeled data. Despite impressive …

Abstract Referring Image Segmentation (RIS) aims to segment objects from an image based
on a language description. Recent advancements have introduced transformer-based …