Explore how 2D and 3D object detection works, their key differences, and their applications in fields like autonomous vehicles, robotics, and augmented reality.

Papers, code and datasets about deep learning for 3D Object Detection.

Apr 25, 2025 · We review key architectures, pretraining strategies, and prompt engineering methods that align textual and 3D features for effective 3D object detection with vision …

3D object detection is a computer vision task that identifies and localizes objects in three dimensions. It estimates each object’s position, size, and orientation in space.

Sep 10, 2024 · This work investigates the most recent 3D object detection methods for self-driving cars, emphasizing the importance of advanced deep learning models and multi-sensor fusion …

Mar 13, 2025 · This study presents PillarFocusNet, a novel network about 3D point cloud object detection that optimizes the PointPillars framework to improve detection performance.

This paper presents a comparative review of recent 2D and 3D detection models, focusing on their occlusion-handling capabilities and the impact of sensor modalities such as stereo vision, …

Jun 10, 2025 · Three-dimensional object detection aims to detect the 3D properties of objects in the input data provided by sensors in the data collection environment. By using sensors like …

We present 3DiffTection, a cutting-edge method for 3D detection from single images, grounded in features from a 3D-aware diffusion model. Annotating large-scale image data for 3D object …

MMDetection3D is an open source object detection toolbox based on PyTorch, towards the next-generation platform for general 3D detection. It is a part of the OpenMMLab project.