AV1 motion vectors filtered by cosine consistency yield dense sub-pixel correspondences that support structure-from-motion on short video clips with lower CPU cost and higher match density than sequential SIFT.
Superpoint: Self-supervised interest point de- tection and description
5 Pith papers cite this work. Polarity classification is still indexing.
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abstract
This paper presents a self-supervised framework for training interest point detectors and descriptors suitable for a large number of multiple-view geometry problems in computer vision. As opposed to patch-based neural networks, our fully-convolutional model operates on full-sized images and jointly computes pixel-level interest point locations and associated descriptors in one forward pass. We introduce Homographic Adaptation, a multi-scale, multi-homography approach for boosting interest point detection repeatability and performing cross-domain adaptation (e.g., synthetic-to-real). Our model, when trained on the MS-COCO generic image dataset using Homographic Adaptation, is able to repeatedly detect a much richer set of interest points than the initial pre-adapted deep model and any other traditional corner detector. The final system gives rise to state-of-the-art homography estimation results on HPatches when compared to LIFT, SIFT and ORB.
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use method 1representative citing papers
Gideon is a hardware-aware feature extractor using distillation and DNAS that achieves 111 fps on STM32N6 under 1.5 MB memory with negligible INT8 quantization loss.
Digital Cousins is a generative real-to-sim method that creates diverse high-fidelity simulation scenes from real panoramas to improve generalization in robot learning and evaluation.
An automated annotation pipeline combining Grounded DINO and SAM produces usable bounding boxes and masks for weakly supervised defect detection in shearography.
EBOD integrates SAM3 with DINOv3 and LightGlue to leverage previous error examples and suppress recurring false positives and negatives without retraining.
citing papers explorer
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Leveraging AV1 motion vectors for Fast and Dense Feature Matching
AV1 motion vectors filtered by cosine consistency yield dense sub-pixel correspondences that support structure-from-motion on short video clips with lower CPU cost and higher match density than sequential SIFT.
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Hardware-Aware Neural Feature Extraction for Resource-Constrained Devices
Gideon is a hardware-aware feature extractor using distillation and DNAS that achieves 111 fps on STM32N6 under 1.5 MB memory with negligible INT8 quantization loss.
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From Seeing to Simulating: Generative High-Fidelity Simulation with Digital Cousins for Generalizable Robot Learning and Evaluation
Digital Cousins is a generative real-to-sim method that creates diverse high-fidelity simulation scenes from real panoramas to improve generalization in robot learning and evaluation.
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Automated Annotation of Shearographic Measurements Enabling Weakly Supervised Defect Detection
An automated annotation pipeline combining Grounded DINO and SAM produces usable bounding boxes and masks for weakly supervised defect detection in shearography.
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Example-Based Object Detection
EBOD integrates SAM3 with DINOv3 and LightGlue to leverage previous error examples and suppress recurring false positives and negatives without retraining.