YOLO has become a central real-time object detection system for robotics, driverless cars,
and video monitoring applications. We present a comprehensive analysis of YOLO's …

This paper surveys research works in the quickly advancing field of instruction tuning (IT),
which can also be referred to as supervised fine-tuning (SFT)\footnote {In this paper, unless …

Today's deep learning methods focus on how to design the objective functions to make the
prediction as close as possible to the target. Meanwhile, an appropriate neural network …

Since its inception in 2015, the YOLO (You Only Look Once) variant of object detectors has
rapidly grown, with the latest release of YOLO-v8 in January 2023. YOLO variants are …

We present ODISE: Open-vocabulary DIffusion-based panoptic SEgmentation, which unifies
pre-trained text-image diffusion and discriminative models to perform open-vocabulary …

We present Segment Anything Model 2 (SAM 2), a foundation model towards solving
promptable visual segmentation in images and videos. We build a data engine, which …

Abstract We present Visual AutoRegressive modeling (VAR), a new generation paradigm
that redefines the autoregressive learning on images as coarse-to-fine" next-scale …

Abstract The You Only Look Once (YOLO) series of detectors have established themselves
as efficient and practical tools. However their reliance on predefined and trained object …

In computer vision, a series of exemplary advances have been made in several areas
involving image classification, semantic segmentation, object detection, and image super …

In the past years, YOLO-series models have emerged as the leading approaches in the area
of real-time object detection. Many studies pushed up the baseline to a higher level by …