16.11.2021 · YolactEdge: Real-time Instance Segmentation on the Edge. YolactEdge, the first competitive instance segmentation approach that runs on small edge devices at real-time speeds. Specifically, YolactEdge runs at up to 30.8 FPS on a Jetson AGX Xavier (and 172.7 FPS on an RTX 2080 Ti) with a ResNet-101 backbone on 550×550 resolution images.
Real-time Instance Segmentation Daniel Bolya Chong Zhou Fanyi Xiao Yong Jae Lee University of California, Davis {dbolya, cczhou, fyxiao, yongjaelee}@ucdavis.edu Abstract We present a simple, fully-convolutional model for real-time instance segmentation that achieves 29.8 mAP on MS COCO at 33.5 fps evaluated on a single Titan Xp, which is
We present a simple, fully-convolutional model for real- time instance segmentation that achieves 29.8 mAP on MS. COCO at 33.5 fps evaluated on a single ...
We present a simple, fully-convolutional model for real-time ( $>30$ > 30 fps) instance segmentation that achieves competitive results on MS COCO evaluated ...
Real-Time Instance Segmentation Tracking Algorithm in Mixed Reality. Abstract: In a mixed reality environment, in order to complete the interaction of ...
Browse machine learning models and code for Real Time Instance Segmentation to catalyze your projects, and easily connect with engineers and experts when ...
Real-time Instance Segmentation. 14 papers with code • 4 benchmarks • 3 datasets. Similar to its parent task, instance segmentation, but with the goal of achieving real-time capabilities under a defined setting. Image Credit: SipMask: …
We present a simple, fully-convolutional model for real-time ( fps) instance segmentation that achieves competitive results on MS COCO evaluated on a single Titan Xp, which is significantly faster than any previous state-of-the-art approach. Moreover, we …
We present a simple, fully-convolutional model for realtime instance segmentation that achieves 29.8 mAP on MS COCO at 33 fps evaluated on a single Titan Xp ...