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Fine-grained Action Recognition

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Showing 1–38 of 38 papers

TitleStatusHype
Revealing Single Frame Bias for Video-and-Language LearningCode2
Understanding Long Videos with Multimodal Language ModelsCode2
What and How Well You Performed? A Multitask Learning Approach to Action Quality AssessmentCode1
Few-shot Action Recognition with Prototype-centered Attentive LearningCode1
Sharing Pain: Using Pain Domain Transfer for Video Recognition of Low Grade Orthopedic Pain in HorsesCode1
SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning StabilizationCode1
Video Pose Distillation for Few-Shot, Fine-Grained Sports Action RecognitionCode1
Multi-Modal Domain Adaptation for Fine-Grained Action RecognitionCode1
Attention-Based Context Aware Reasoning for Situation RecognitionCode1
Higher-order Pooling of CNN Features via Kernel Linearization for Action Recognition—0
HuMMan: Multi-Modal 4D Human Dataset for Versatile Sensing and Modeling—0
Adaptive Recursive Circle Framework for Fine-grained Action Recognition—0
Learning Discriminative Motion Features Through Detection—0
M^3Net: Multi-view Encoding, Matching, and Fusion for Few-shot Fine-grained Action Recognition—0
Multi-Dimensional Refinement Graph Convolutional Network with Robust Decouple Loss for Fine-Grained Skeleton-Based Action Recognition—0
Object Properties Inferring from and Transfer for Human Interaction Motions—0
Interaction Part Mining: A Mid-Level Approach for Fine-Grained Action Recognition—0
A Review on Coarse to Fine-Grained Animal Action Recognition—0
Are Visual-Language Models Effective in Action Recognition? A Comparative Study—0
A Simple and Efficient Baseline for Video Action Recognition—0
Combined CNN Transformer Encoder for Enhanced Fine-grained Human Action Recognition—0
Dynamic Spatio-Temporal Specialization Learning for Fine-Grained Action Recognition—0
FACTS: Fine-Grained Action Classification for Tactical Sports—0
FinePseudo: Improving Pseudo-Labelling through Temporal-Alignablity for Semi-Supervised Fine-Grained Action Recognition—0
Flow Dynamics Correction for Action Recognition—0
Segmental Spatiotemporal CNNs for Fine-grained Action Segmentation—0
Team VI-I2R Technical Report on EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2021—0
Train, Diagnose and Fix: Interpretable Approach for Fine-grained Action Recognition—0
Understanding Video Transformers via Universal Concept Discovery—0
Analysis of Hand Segmentation in the WildCode0
Few-Shot Fine-Grained Action Recognition via Bidirectional Attention and Contrastive Meta-LearningCode0
Unsupervised Feature Learning of Human Actions as Trajectories in Pose Embedding ManifoldCode0
ConvGRU in Fine-grained Pitching Action Recognition for Action Outcome PredictionCode0
Enhancing Action Recognition by Leveraging the Hierarchical Structure of Actions and Textual ContextCode0
Pre-training for Action Recognition with Automatically Generated Fractal DatasetsCode0
Real-time Action Recognition for Fine-Grained Actions and The Hand Wash DatasetCode0
HalluciNet-ing Spatiotemporal Representations Using a 2D-CNNCode0
Fine-grained Action Analysis: A Multi-modality and Multi-task Dataset of Figure SkatingCode0
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