V3Det Challenge 2024 on Vast Vocabulary and Open Vocabulary Object Detection: Methods and Results

在现实场景中检测物体是一项复杂的任务，由于涉及到各种挑战，包括物体种类的广泛范围以及可能遇到以前未知或未见过的物体。这些挑战需要开发公共基准和挑战来推进物体检测领域的发展。受以前COCO和LVIS挑战的成功启发，我们将在2024年与第四届Open World Vision Workshop: Visual Perception via Learning in an Open World (VPLOW)在美国西雅图举办V3Det Challenge 2024。这个挑战旨在推动物体检测研究的界限，鼓励这个领域的创新。V3Det Challenge 2024包括两个赛道：1）广泛词汇物体检测：这个赛道专注于从13204个类别的大量物体中检测物体，测试检测算法识别和定位多样化物体的能力。2）开放词汇物体检测：这个赛道更进一步，要求算法从一组开放的类别中检测物体，包括未知的物体。在接下来的章节中，我们将提供参与者提交的解决方案的综合摘要和分析。通过分析所呈现的方法和解决方案，我们旨在激发广泛词汇和开放词汇物体检测的未来研究方向，推动这个领域的进步。挑战主页：https://v3det.openxlab.org.cn/challenge。

V3Det Challenge 2024 aims to push the boundaries of object detection research and encourage innovation in this field by organizing two tracks: Vast Vocabulary Object Detection and Open Vocabulary Object Detection.

The challenge tests the detection algorithm's ability to recognize and locate diverse objects from a large set of categories, including unknown objects in an open set.

The challenge is organized in conjunction with the 4th Open World Vision Workshop: Visual Perception via Learning in an Open World (VPLOW) at CVPR 2024, Seattle, US. The challenge homepage provides comprehensive information about the challenge and the datasets used. The challenge encourages innovation in object detection and aims to inspire future research directions.

Recent related research in this field includes COCO and LVIS Challenges, which have inspired the V3Det Challenge 2024. Other related research includes papers on object detection using deep learning, such as 'Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks' and 'You Only Look Once: Unified, Real-Time Object Detection'.