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Action Recognition In Videos
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Action Recognition in Videos is a task in computer vision and pattern recognition where the goal is to identify and categorize human actions performed in a video sequence. The task involves analyzing the spatiotemporal dynamics of the actions and mapping them to a predefined set of action classes, such as running, jumping, or swimming.
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이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Vision and Intention Boost Large Language Model in Long-Term Action Anticipation
Hierarchical and Multimodal Data for Daily Activity Understanding
Action Anticipation from SoccerNet Football Video Broadcasts
Body-Hand Modality Expertized Networks with Cross-attention for Fine-grained Skeleton Action Recognition
ICPR 2024 Competition on Rider Intention Prediction
Learning to Generate Long-term Future Narrations Describing Activities of Daily Living
Multimodal Large Models Are Effective Action Anticipators
Temporal Context Consistency Above All: Enhancing Long-Term Anticipation by Learning and Enforcing Temporal Constraints
ActFusion: a Unified Diffusion Model for Action Segmentation and Anticipation
HiMemFormer: Hierarchical Memory-Aware Transformer for Multi-Agent Action Anticipation
Human Action Anticipation: A Survey
VEDIT: Latent Prediction Architecture For Procedural Video Representation Learning
Mamba Fusion: Learning Actions Through Questioning
EPAM-Net: An Efficient Pose-driven Attention-guided Multimodal Network for Video Action Recognition
From Recognition to Prediction: Leveraging Sequence Reasoning for Action Anticipation
User-in-the-loop Evaluation of Multimodal LLMs for Activity Assistance
QuIIL at T3 challenge: Towards Automation in Life-Saving Intervention Procedures from First-Person View
Gated Temporal Diffusion for Stochastic Long-Term Dense Anticipation
QueryMamba: A Mamba-Based Encoder-Decoder Architecture with a Statistical Verb-Noun Interaction Module for Video Action Forecasting @ Ego4D Long-Term Action Anticipation Challenge 2024
Semantically Guided Representation Learning For Action Anticipation
EgoVideo: Exploring Egocentric Foundation Model and Downstream Adaptation
VLM Agents Generate Their Own Memories: Distilling Experience into Embodied Programs of Thought
Can't make an Omelette without Breaking some Eggs: Plausible Action Anticipation using Large Video-Language Models
The impact of Compositionality in Zero-shot Multi-label action recognition for Object-based tasks
PhilHumans: Benchmarking Machine Learning for Personal Health
Simba: Mamba augmented U-ShiftGCN for Skeletal Action Recognition in Videos
Gaze-Guided Graph Neural Network for Action Anticipation Conditioned on Intention
ActNetFormer: Transformer-ResNet Hybrid Method for Semi-Supervised Action Recognition in Videos
EgoExoLearn: A Dataset for Bridging Asynchronous Ego- and Exo-centric View of Procedural Activities in Real World
Intention Action Anticipation Model with Guide-Feedback Loop Mechanism
Deep Learning Approaches for Human Action Recognition in Video Data
On the Efficacy of Text-Based Input Modalities for Action Anticipation
HaltingVT: Adaptive Token Halting Transformer for Efficient Video Recognition
DVANet: Disentangling View and Action Features for Multi-View Action Recognition
Action Scene Graphs for Long-Form Understanding of Egocentric Videos
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