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Action Recognition

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하위 태스크: 15
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Action Recognition is a computer vision task that involves recognizing human actions in videos or images. The goal is to classify and categorize the actions being performed in the video or image into a predefined set of action classes.

In the video domain, it is an open question whether training an action classification network on a sufficiently large dataset, will give a similar boost in performance when applied to a different temporal task or dataset. The challenges of building video datasets has meant that most popular benchmarks for action recognition are small, having on the order of 10k videos.

Please note some benchmarks may be located in the Action Classification or Video Classification tasks, e.g. Kinetics-400.

논문

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Action Recognition

논문

A Causal Lens for Evaluating Faithfulness Metrics

EgoSim: An Egocentric Multi-view Simulator and Real Dataset for Body-worn Cameras during Motion and Activity

Trunk-branch Contrastive Network with Multi-view Deformable Aggregation for Multi-view Action Recognition

FLEKE: Federated Locate-then-Edit Knowledge Editing

Edit Once, Update Everywhere: A Simple Framework for Cross-Lingual Knowledge Synchronization in LLMs

Revealing and Mitigating Over-Attention in Knowledge Editing

Online hand gesture recognition using Continual Graph Transformers

CoME: An Unlearning-based Approach to Conflict-free Model Editing

SNN-Driven Multimodal Human Action Recognition via Event Camera and Skeleton Data Fusion

MomentSeeker: A Task-Oriented Benchmark For Long-Video Moment Retrieval

Activation-wise Propagation: A Universal Strategy to Break Timestep Constraints in Spiking Neural Networks for 3D Data Processing

DELMAN: Dynamic Defense Against Large Language Model Jailbreaking with Model Editing

Personality Editing for Language Models through Relevant Knowledge Editing

The Mirage of Model Editing: Revisiting Evaluation in the Wild

K-Edit: Language Model Editing with Contextual Knowledge Awareness

Enhancing Video Understanding: Deep Neural Networks for Spatiotemporal Analysis

MEMIT-Merge: Addressing MEMIT's Key-Value Conflicts in Same-Subject Batch Editing for LLMs

From Image to Video: An Empirical Study of Diffusion Representations

Reinforced Lifelong Editing for Language Models

HyLiFormer: Hyperbolic Linear Attention for Skeleton-based Human Action Recognition

Injecting Universal Jailbreak Backdoors into LLMs in Minutes

AnyEdit: Edit Any Knowledge Encoded in Language Models

Related Knowledge Perturbation Matters: Rethinking Multiple Pieces of Knowledge Editing in Same-Subject

Cross-Encoder Rediscovers a Semantic Variant of BM25

MD-BERT: Action Recognition in Dark Videos via Dynamic Multi-Stream Fusion and Temporal Modeling

HD-EPIC: A Highly-Detailed Egocentric Video Dataset

Position: Editing Large Language Models Poses Serious Safety Risks

Kronecker Mask and Interpretive Prompts are Language-Action Video Learners

Mass-Editing Memory with Attention in Transformers: A cross-lingual exploration of knowledge

IMDPrompter: Adapting SAM to Image Manipulation Detection by Cross-View Automated Prompt Learning

Efficient Model Editing with Task Vector Bases: A Theoretical Framework and Scalable Approach

Lifelong Knowledge Editing requires Better Regularization

Building Bridges, Not Walls -- Advancing Interpretability by Unifying Feature, Data, and Model Component Attribution

XRF V2: A Dataset for Action Summarization with Wi-Fi Signals, and IMUs in Phones, Watches, Earbuds, and Glasses

ALBAR: Adversarial Learning approach to mitigate Biases in Action Recognition

Advances in Multimodal Adaptation and Generalization: From Traditional Approaches to Foundation Models