Abstract: 3D classification is complex and challenging because of high-dimensional data, the intricate nature of their spatial relationships, and viewpoint variations. We fill the gap in view-based 3D ...

This is the official PyTorch implementation of the paper DDet3D: Embracing 3D Object Detector with Diffusion, by Gopi Krishna Erabati and Helder Araujo. Existing approaches rely on heuristic or ...

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Apple is turning the flat photo into a new computing primitive. With its SHARP model, the company says a single snapshot can be transformed into a navigable 3D scene in less than a second on standard ...

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...

Meta Platforms Inc. today is expanding its suite of open-source Segment Anything computer vision models with the release of SAM 3 and SAM 3D, introducing enhanced object recognition and ...

We’re introducing SAM 3 and SAM 3D, the newest additions to our Segment Anything Collection, which advance AI understanding of the visual world. SAM 3 enables detection and tracking of objects in ...

If you find 3D printers to be just a little too coldly futuristic, this contraption might be more to your liking. Scientists from Cornell University have created a machine that knits solid 3D objects ...

What if the physical world could be captured with such precision that it became indistinguishable from its digital counterpart? This is the bold ambition driving the collaboration between Microsoft ...

conda create -n ovmono3d python=3.8.20 conda activate ovmono3d pip install torch==2.4.1 torchvision==0.19.1 --index-url https://download.pytorch.org/whl/cu121 to ...

Autonomous driving is the future trend. Accurate 3D object detection is a prerequisite for achieving autonomous driving. Currently, 3D object detection relies on three main sensors: monocular cameras, ...