  Detecting objects in real-world scenes is a complex task due to various
challenges, including the vast range of object categories, and potential
encounters with previously unknown or unseen objects. The challenges
necessitate the development of public benchmarks and challenges to advance the
field of object detection. Inspired by the success of previous COCO and LVIS
Challenges, we organize the V3Det Challenge 2024 in conjunction with the 4th
Open World Vision Workshop: Visual Perception via Learning in an Open World
(VPLOW) at CVPR 2024, Seattle, US. This challenge aims to push the boundaries
of object detection research and encourage innovation in this field. The V3Det
Challenge 2024 consists of two tracks: 1) Vast Vocabulary Object Detection:
This track focuses on detecting objects from a large set of 13204 categories,
testing the detection algorithm's ability to recognize and locate diverse
objects. 2) Open Vocabulary Object Detection: This track goes a step further,
requiring algorithms to detect objects from an open set of categories,
including unknown objects. In the following sections, we will provide a
comprehensive summary and analysis of the solutions submitted by participants.
By analyzing the methods and solutions presented, we aim to inspire future
research directions in vast vocabulary and open-vocabulary object detection,
driving progress in this field. Challenge homepage:
https://v3det.openxlab.org.cn/challenge
