Zero Shot Action Recognition On Ucf101

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Top-1 Accuracy

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이 벤치마크에서 각 모델의 성능 결과

		Paper Title
OTI(ViT-L/14)	92.8	Orthogonal Temporal Interpolation for Zero-Shot Video Recognition
IMP-MoE-L	91.5	Alternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception
MOV (ViT-L/14)	87.1	Multimodal Open-Vocabulary Video Classification via Pre-Trained Vision and Language Models
BIKE	86.6	Bidirectional Cross-Modal Knowledge Exploration for Video Recognition with Pre-trained Vision-Language Models
VideoCoCa	86.6	VideoCoCa: Video-Text Modeling with Zero-Shot Transfer from Contrastive Captioners
Text4Vis	85.8	Revisiting Classifier: Transferring Vision-Language Models for Video Recognition
TC-CLIP	85.4	Leveraging Temporal Contextualization for Video Action Recognition
EVA-CLIP-E/14+	83.1	EVA-CLIP: Improved Training Techniques for CLIP at Scale
MOV (ViT-B/16)	82.6	Multimodal Open-Vocabulary Video Classification via Pre-Trained Vision and Language Models
OST	79.7	OST: Refining Text Knowledge with Optimal Spatio-Temporal Descriptor for General Video Recognition
EZ-CLIP	79.1	EZ-CLIP: Efficient Zeroshot Video Action Recognition
MAXI	78.2	MAtch, eXpand and Improve: Unsupervised Finetuning for Zero-Shot Action Recognition with Language Knowledge
LoCATe-GAT	76.0	LoCATe-GAT: Modeling Multi-Scale Local Context and Action Relationships for Zero-Shot Action Recognition
VicTR (ViT-B/16)	72.4	VicTR: Video-conditioned Text Representations for Activity Recognition
X-CLIP	72.0	Expanding Language-Image Pretrained Models for General Video Recognition
ResT	58.7	Cross-modal Representation Learning for Zero-shot Action Recognition
AURL	58	Alignment-Uniformity aware Representation Learning for Zero-shot Video Classification
JigsawNet	56.0	Rethinking Zero-shot Action Recognition: Learning from Latent Atomic Actions
CLASTER	53.9	CLASTER: Clustering with Reinforcement Learning for Zero-Shot Action Recognition
ER-ZSAR	51.8	Elaborative Rehearsal for Zero-shot Action Recognition

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Zero Shot Action Recognition On Ucf101

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