xingyizhou/ExtremeNet: Bottom-up Object Detection by Grouping Extreme and Center Points

Bottom-up Object Detection by Grouping Extreme and Center Points

saved by

• Alexander Davies

related reading

• GitHub - david8862/keras-YOLOv3-model-set: end-to-end YOLOv4/v3/v2 object detection pipeline, implemented on tf.keras with different technologies · GitHubgithub.com
• GitHub - Masao-Taketani/FOTS_OCR: TensorFlow Implementation of FOTS, Fast Oriented Text Spotting with a Unified Network. · GitHubgithub.com
• Convex hull, Image processing, Image Classification, Image retrieval, Shape detectiondiva-portal.org
• ReferIt3D: Neural Listeners for Fine-Grained 3D Object Identification in Real-World Scenesecva.net
• GitHub - open-edge-platform/anomalib: An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference. · GitHubgithub.com
• IEEE Xplore Full-Text PDF:ieeexplore.ieee.org
• Parsed | Custom, interpretable AI systems that continuously learnparsed.com
• ML Contestsmlcontests.com
• Humanoid Indexhumanoid-index.com
• Reference for ultralytics/trackers/bot_sort.py | Ultralytics Docsdocs.ultralytics.com
• GitHub - ByteByteGoHq/system-design-101: Explain complex systems using visuals and simple terms. Help you prepare for system design interviews. · GitHubgithub.com
• GitHub - NVlabs/AutoGaze: AutoGaze automatically removes redundant patches in a video, reducing #tokens in ViT/MLLM by 4x-100x. · GitHubgithub.com