Recently integrating video foundation models and large language models to build a video
understanding system can overcome the limitations of specific pre-defined vision tasks. Yet …

In this paper, we propose a long-sequence modeling framework, named StreamPETR, for
multi-view 3D object detection. Built upon the sparse query design in the PETR series, we …

Multi-object tracking (MOT) aims at estimating bounding boxes and identities of objects in
videos. Most methods obtain identities by associating detection boxes whose scores are …

Kalman filter (KF) based methods for multi-object tracking (MOT) make an assumption that
objects move linearly. While this assumption is acceptable for very short periods of …

In this paper, we propose MOTRv2, a simple yet effective pipeline to bootstrap end-to-end
multi-object tracking with a pretrained object detector. Existing end-to-end methods, eg …

The main challenge of Multi-Object Tracking (MOT) lies in maintaining a continuous
trajectory for each target. Existing methods often learn reliable motion patterns to match the …

Tracking objects over long videos effectively means solving a spectrum of problems, from
short-term association for un-occluded objects to long-term association for objects that are …

As a video task, Multiple Object Tracking (MOT) is expected to capture temporal information
of targets effectively. Unfortunately, most existing methods only explicitly exploit the object …

This paper presents a vector HD-map** algorithm that formulates the map** as a
tracking task and uses a history of memory latents to ensure consistent reconstructions over …

The handling of long videos with complex and occluded sequences has recently emerged
as a new challenge in the video instance segmentation (VIS) community. However, existing …