https://github.com/LeegoChen/PTC-Net
PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
A methodology that involves selecting relevant data or examples from a large dataset to support tasks like prediction, learning, or inference. It enhances models by providing context or additional information, often used in systems like retrieval-augmented generation or in-context learning.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition
Deep Visual-Semantic Alignments for Generating Image Descriptions
Graph Matching Networks for Learning the Similarity of Graph Structured Objects
Learning Compressed Sentence Representations for On-Device Text Processing
SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
Beyond Two-Tower Matching: Learning Sparse Retrievable Cross-Interactions for Recommendation
RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing
UMT: Unified Multi-modal Transformers for Joint Video Moment Retrieval and Highlight Detection
Adversarial Autoencoders for Compact Representations of 3D Point Clouds
SCDV : Sparse Composite Document Vectors using soft clustering over distributional representations
Algorithmic Guarantees for Inverse Imaging with Untrained Network Priors
PACRR: A Position-Aware Neural IR Model for Relevance Matching
TMR: Text-to-Motion Retrieval Using Contrastive 3D Human Motion Synthesis
Learning Deep Representations of Fine-grained Visual Descriptions
TopiOCQA: Open-domain Conversational Question Answering with Topic Switching
Learning Disentangled Representations via Mutual Information Estimation
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
Contrastive Learning of Medical Visual Representations from Paired Images and Text
Simplified TinyBERT: Knowledge Distillation for Document Retrieval
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
Beyond Part Models: Person Retrieval with Refined Part Pooling (and a Strong Convolutional Baseline)
SpaDE: Improving Sparse Representations using a Dual Document Encoder for First-stage Retrieval
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.