https://github.com/huanglianghua/GlobalTrack
공식 코드GlobalTrack: A Simple and Strong Baseline for Long-term Tracking
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Visual Instance Search is the task of retrieving from a database of images the ones that contain an instance of a visual query. It is typically much more challenging than finding images from the database that contain objects belonging to the same category as the object in the query. If the visual query is an image of a shoe, visual Instance Search does not try to find images of shoes, which might differ from the query in shape, color or size, but tries to find images of the exact same shoe as the one in the query image. Visual Instance Search challenges image representations as the features extracted from the images must enable such fine-grained recognition despite variations in viewpoints, scale, position, illumination, etc. Whereas holistic image representations, where each image is mapped to a single high-dimensional vector, are sufficient for coarse-grained similarity retrieval, local features are needed for instance retrieval.
Source: Dynamicity and Durability in Scalable Visual Instance Search
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
GlobalTrack: A Simple and Strong Baseline for Long-term Tracking
Bags of Local Convolutional Features for Scalable Instance Search
Class-Weighted Convolutional Features for Visual Instance Search
The Effect of Points Dispersion on the $k$-nn Search in Random Projection Forests
Neural Audio Fingerprint for High-specific Audio Retrieval based on Contrastive Learning
Confidence-Aware Active Feedback for Interactive Instance Search
Bags of Local Convolutional Features for Scalable Instance Search
Saliency Weighted Convolutional Features for Instance Search
Data-efficient End-to-end Information Extraction for Statistical Legal Analysis
Neural Audio Fingerprint for High-specific Audio Retrieval based on Contrastive Learning
Neural Audio Fingerprint for High-specific Audio Retrieval based on Contrastive Learning
Class-Weighted Convolutional Features for Visual Instance Search
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.