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Found 8 papers, 4 papers with code
AnyOKP: One-Shot and Instance-Aware Object Keypoint Extraction with Pretrained ViT
Towards flexible object-centric visual perception, we propose a one-shot instance-aware object keypoint (OKP) extraction approach, AnyOKP, which leverages the powerful representation ability of pretrained vision transformer (ViT), and can obtain keypoints on multiple object instances of arbitrary category after learning from a support image.
MVSTER: Epipolar Transformer for Efficient Multi-View Stereo
Therefore, we present MVSTER, which leverages the proposed epipolar Transformer to learn both 2D semantics and 3D spatial associations efficiently.
ELSD: Efficient Line Segment Detector and Descriptor
The line description ability of ELSD also outperforms the previous works on the line matching task.
Ranked #1 on
Line Segment Detection
on wireframe dataset
Multi-frame Feature Aggregation for Real-time Instrument Segmentation in Endoscopic Video
However, the high computation cost may limit the application of deep models to time-sensitive tasks such as online surgical video analysis for robotic-assisted surgery.
Contour Primitive of Interest Extraction Network Based on One-Shot Learning for Object-Agnostic Vision Measurement
For the novel CPI extraction task, we built the Object Contour Primitives dataset using online public images, and the Robotic Object Contour Measurement dataset using a camera mounted on a robot.
TP-LSD: Tri-Points Based Line Segment Detector
To realize one-step detection with a faster and more compact model, we introduce the tri-points representation, converting the line segment detection to the end-to-end prediction of a root-point and two endpoints for each line segment.
Ranked #2 on
Line Segment Detection
on York Urban Dataset
LC-GAN: Image-to-image Translation Based on Generative Adversarial Network for Endoscopic Images
For live image segmentation, we first translate the live images to fake-cadaveric images with LC-GAN and then perform segmentation on the fake-cadaveric images with models trained on the real cadaveric dataset.
Towards Better Surgical Instrument Segmentation in Endoscopic Vision: Multi-Angle Feature Aggregation and Contour Supervision
Accurate and real-time surgical instrument segmentation is important in the endoscopic vision of robot-assisted surgery, and significant challenges are posed by frequent instrument-tissue contacts and continuous change of observation perspective.
