https://github.com/SforAiDl/CountCLIP
Learning Transferable Visual Models From Natural Language Supervision
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Open-vocabulary detection (OVD) aims to generalize beyond the limited number of base classes labeled during the training phase. The goal is to detect novel classes defined by an unbounded (open) vocabulary at inference.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
X-Paste: Revisiting Scalable Copy-Paste for Instance Segmentation using CLIP and StableDiffusion
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Seg-Zero: Reasoning-Chain Guided Segmentation via Cognitive Reinforcement
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Learning Transferable Visual Models From Natural Language Supervision
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
Learning Transferable Visual Models From Natural Language Supervision
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.