Object detection, as of one the most fundamental and challenging problems in computer
vision, has received great attention in recent years. Over the past two decades, we have …

Change detection is an essential and widely utilized task in remote sensing that aims to
detect and analyze changes occurring in the same geographical area over time, which has …

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 …

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

Current universal segmentation methods demonstrate strong capabilities in pixel-level
image and video understanding. However, they lack reasoning abilities and cannot be …

Video segmentation aims to segment and track every pixel in diverse scenarios accurately.
In this paper, we present Tube-Link, a versatile framework that addresses multiple core tasks …

In this paper we address the challenge of image resolution variation for the Segment
Anything Model (SAM). SAM known for its zero-shot generalizability exhibits a performance …

Multi-object tracking (MOT) requires detecting and associating objects through frames.
Unlike tracking via detected bounding boxes or center points, we propose tracking objects …

In this work, we focus on open vocabulary instance segmentation to expand a segmentation
model to classify and segment instance-level novel categories. Previous approaches have …

Remote sensing (RS) spatiotemporal prediction aims to infer future trends from historical
spatiotemporal data, eg, videos and time-series images, which has a broad application …