https://github.com/tigerchen52/qrneuron
공식 코드Identifying Query-Relevant Neurons in Large Language Models for Long-Form Texts
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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.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Identifying Query-Relevant Neurons in Large Language Models for Long-Form Texts
VideoMoCo: Contrastive Video Representation Learning with Temporally Adversarial Examples
Semi-Supervised Classification with Graph Convolutional Networks
Compressing Recurrent Neural Networks with Tensor Ring for Action Recognition
Net2Brain: A Toolbox to compare artificial vision models with human brain responses
Temporal-Relational CrossTransformers for Few-Shot Action Recognition
Interpreting and Controlling Vision Foundation Models via Text Explanations
Learning Implicit Temporal Alignment for Few-shot Video Classification
Spatiotemporal Tile-based Attention-guided LSTMs for Traffic Video Prediction
TWLV-I: Analysis and Insights from Holistic Evaluation on Video Foundation Models
SpikMamba: When SNN meets Mamba in Event-based Human Action Recognition
Contextual Explainable Video Representation: Human Perception-based Understanding
DirecFormer: A Directed Attention in Transformer Approach to Robust Action Recognition
Efficient Model Editing with Task Vector Bases: A Theoretical Framework and Scalable Approach
Model Editing as a Robust and Denoised variant of DPO: A Case Study on Toxicity
Real-Time Multimodal Cognitive Assistant for Emergency Medical Services
Can Sensitive Information Be Deleted From LLMs? Objectives for Defending Against Extraction Attacks
Global Semantic Descriptors for Zero-Shot Action Recognition
Tell me what you see: A zero-shot action recognition method based on natural language descriptions
Spiking Neural Networks for event-based action recognition: A new task to understand their advantage
TEAM-Net: Multi-modal Learning for Video Action Recognition with Partial Decoding
Surg-3M: A Dataset and Foundation Model for Perception in Surgical Settings
VLKEB: A Large Vision-Language Model Knowledge Editing Benchmark
Handwashing Action Detection System for an Autonomous Social Robot
Why Can't I Dance in the Mall? Learning to Mitigate Scene Bias in Action Recognition
Learning Representational Invariances for Data-Efficient Action Recognition
Unsupervised Domain Adaptation for Video Transformers in Action Recognition
Benchmarking Micro-action Recognition: Dataset, Methods, and Applications
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.