https://github.com/AnasIbrahim/image_agnostic_segmentation
공식 코드DoUnseen: Tuning-Free Class-Adaptive Object Detection of Unseen Objects for Robotic Grasping
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Zero-shot object detection (ZSD) is the task of object detection where no visual training data is available for some of the target object classes.
<span style="color:grey; opacity: 0.6">( Image credit: Zero-Shot Object Detection: Learning to Simultaneously Recognize and Localize Novel Concepts )</span>
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
DoUnseen: Tuning-Free Class-Adaptive Object Detection of Unseen Objects for Robotic Grasping
ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models
Robust Region Feature Synthesizer for Zero-Shot Object Detection
Zero-shot Object Detection Through Vision-Language Embedding Alignment
ELEVATER: A Benchmark and Toolkit for Evaluating Language-Augmented Visual Models
Efficient Feature Distillation for Zero-shot Annotation Object Detection
Efficient Feature Distillation for Zero-shot Annotation Object Detection
VisionReasoner: Unified Visual Perception and Reasoning via Reinforcement Learning
VisionReasoner: Unified Visual Perception and Reasoning via Reinforcement Learning
VisionReasoner: Unified Visual Perception and Reasoning via Reinforcement Learning
DINO-X: A Unified Vision Model for Open-World Object Detection and Understanding
Grounding DINO 1.5: Advance the "Edge" of Open-Set Object Detection
Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection
T-Rex2: Towards Generic Object Detection via Text-Visual Prompt Synergy
Synthesizing Knowledge-enhanced Features for Real-world Zero-shot Food Detection
SeeDS: Semantic Separable Diffusion Synthesizer for Zero-shot Food Detection
Learning Open-World Object Proposals without Learning to Classify
Real-time Transformer-based Open-Vocabulary Detection with Efficient Fusion Head
No Annotations for Object Detection in Art through Stable Diffusion
Resolving Semantic Confusions for Improved Zero-Shot Detection
ViLLA: Fine-Grained Vision-Language Representation Learning from Real-World Data
Open-vocabulary Object Detection via Vision and Language Knowledge Distillation
Open-vocabulary Object Detection via Vision and Language Knowledge Distillation
OV-DINO: Unified Open-Vocabulary Detection with Language-Aware Selective Fusion
DetToolChain: A New Prompting Paradigm to Unleash Detection Ability of MLLM
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.