Papers with Code 아카이브
Zero-Shot Action Recognition
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Can masking background and object reduce static bias for zero-shot action recognition?
Building a Multi-modal Spatiotemporal Expert for Zero-shot Action Recognition with CLIP
LoCATe-GAT: Modeling Multi-Scale Local Context and Action Relationships for Zero-Shot Action Recognition
TDSM: Triplet Diffusion for Skeleton-Text Matching in Zero-Shot Action Recognition
Zero-Shot Action Recognition in Surveillance Videos
Continual Learning Improves Zero-Shot Action Recognition
Zero-Shot Skeleton-based Action Recognition with Dual Visual-Text Alignment
Text-Enhanced Zero-Shot Action Recognition: A training-free approach
Part-aware Unified Representation of Language and Skeleton for Zero-shot Action Recognition
An Information Compensation Framework for Zero-Shot Skeleton-based Action Recognition
A Cross-Dataset Study for Text-based 3D Human Motion Retrieval
The impact of Compositionality in Zero-shot Multi-label action recognition for Object-based tasks
Leveraging Temporal Contextualization for Video Action Recognition
Fine-Grained Side Information Guided Dual-Prompts for Zero-Shot Skeleton Action Recognition
ActionHub: A Large-scale Action Video Description Dataset for Zero-shot Action Recognition
EZ-CLIP: Efficient Zeroshot Video Action Recognition
OST: Refining Text Knowledge with Optimal Spatio-Temporal Descriptor for General Video Recognition
LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment
Telling Stories for Common Sense Zero-Shot Action Recognition
Orthogonal Temporal Interpolation for Zero-Shot Video Recognition
Actor-agnostic Multi-label Action Recognition with Multi-modal Query
InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation
Alternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception
Synthetic Sample Selection for Generalized Zero-Shot Learning
Vita-CLIP: Video and text adaptive CLIP via Multimodal Prompting
VicTR: Video-conditioned Text Representations for Activity Recognition
EVA-CLIP: Improved Training Techniques for CLIP at Scale
MAtch, eXpand and Improve: Unsupervised Finetuning for Zero-Shot Action Recognition with Language Knowledge
Improving Zero-Shot Action Recognition using Human Instruction with Text Description
Bidirectional Cross-Modal Knowledge Exploration for Video Recognition with Pre-trained Vision-Language Models
VideoCoCa: Video-Text Modeling with Zero-Shot Transfer from Contrastive Captioners
REST: REtrieve & Self-Train for generative action recognition
Global Semantic Descriptors for Zero-Shot Action Recognition
Expanding Language-Image Pretrained Models for General Video Recognition
Multimodal Open-Vocabulary Video Classification via Pre-Trained Vision and Language Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.