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Found 7 papers, 6 papers with code
Infinite Photorealistic Worlds using Procedural Generation
We introduce Infinigen, a procedural generator of photorealistic 3D scenes of the natural world.
Label-Free Synthetic Pretraining of Object Detectors
Our "SOLID" approach consists of two main components: (1) generating synthetic images using a collection of unlabelled 3D models with optimized scene arrangement; (2) pretraining an object detector on "instance detection" task - given a query image depicting an object, detecting all instances of the exact same object in a target image.
Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline
It also outperforms state-of-the-art methods on ScanObjectNN, a real-world point cloud benchmark, and demonstrates better cross-dataset generalization.
Ranked #18 on
Point Cloud Classification
on PointCloud-C
Revisiting Point Cloud Classification with a Simple and Effective Baseline
It also outperforms state-of-the-art methods on ScanObjectNN, a real-world point cloud benchmark, and demonstrates better cross-dataset generalization.
Ranked #11 on
3D Point Cloud Classification
on ModelNet40-C
CornerNet-Lite: Efficient Keypoint Based Object Detection
Together these two variants address the two critical use cases in efficient object detection: improving efficiency without sacrificing accuracy, and improving accuracy at real-time efficiency.
Ranked #137 on
Object Detection
on COCO minival
CornerNet: Detecting Objects as Paired Keypoints
We propose CornerNet, a new approach to object detection where we detect an object bounding box as a pair of keypoints, the top-left corner and the bottom-right corner, using a single convolution neural network.
Ranked #161 on
Object Detection
on COCO test-dev
1-HKUST: Object Detection in ILSVRC 2014
We participated in the object detection track of ILSVRC 2014 and received the fourth place among the 38 teams.
