Papers with Code 아카이브

3D Action Recognition

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하위 태스크

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평가표

3

보존된 평가 기록

13

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/john-hewitt/model-editing-canonical-examples

공식 코드

Model Editing with Canonical Examples

https://github.com/johnnychanv/JailbreakEdit

공식 코드

Injecting Universal Jailbreak Backdoors into LLMs in Minutes

https://github.com/jometeorie/multihopshortcuts

공식 코드

Investigating Multi-Hop Factual Shortcuts in Knowledge Editing of Large Language Models

https://github.com/jx-zhong-for-academic-purpose/kinet

공식 코드

No Pain, Big Gain: Classify Dynamic Point Cloud Sequences with Static Models by Fitting Feature-level Space-time Surfaces

https://github.com/kaai520/PGFA

공식 코드

Zero-shot Skeleton-based Action Recognition with Prototype-guided Feature Alignment

https://github.com/kakashiz/nedb-net

공식 코드

Noise and Edge Based Dual Branch Image Manipulation Detection

https://github.com/kalpitthakkar/pb-gcn

공식 코드

Part-based Graph Convolutional Network for Action Recognition

https://github.com/kathpra/lshr_lsht

공식 코드

Local Spherical Harmonics Improve Skeleton-Based Hand Action Recognition

https://github.com/kawakera-lab/crossmodeltransfer

공식 코드

Cross-Model Transfer of Task Vectors via Few-Shot Orthogonal Alignment

https://github.com/kebii/r2et

공식 코드

Skinned Motion Retargeting with Residual Perception of Motion Semantics & Geometry

https://github.com/keltin13/concept-rot

공식 코드

Concept-ROT: Poisoning Concepts in Large Language Models with Model Editing

https://github.com/kennymckormick/pyskl

공식 코드

PYSKL: Towards Good Practices for Skeleton Action Recognition

https://github.com/kenziyuliu/ms-g3d

공식 코드

Disentangling and Unifying Graph Convolutions for Skeleton-Based Action Recognition

https://github.com/kmeng01/rome

공식 코드

Locating and Editing Factual Associations in GPT

https://github.com/kpeng9510/os-sar

공식 코드

Navigating Open Set Scenarios for Skeleton-based Action Recognition

https://github.com/kpeng9510/proformer

공식 코드

Delving Deep into One-Shot Skeleton-based Action Recognition with Diverse Occlusions

https://github.com/kpeng9510/trans4soar

공식 코드

Delving Deep into One-Shot Skeleton-based Action Recognition with Diverse Occlusions

https://github.com/krystalan/bi_zsre

공식 코드

Cross-Lingual Knowledge Editing in Large Language Models

https://github.com/leiwangr/video-ar

공식 코드

Taylor Videos for Action Recognition

https://github.com/leo-liuzy/propmend

공식 코드

PropMEND: Hypernetworks for Knowledge Propagation in LLMs

https://github.com/levigty/acl

공식 코드

Cross-Model Cross-Stream Learning for Self-Supervised Human Action Recognition

https://github.com/levigty/aimclr

공식 코드

Contrastive Learning from Extremely Augmented Skeleton Sequences for Self-supervised Action Recognition

https://github.com/limaosen0/AS-GCN

공식 코드

Actional-Structural Graph Convolutional Networks for Skeleton-based Action Recognition

https://github.com/lingo-iitgn/xme

공식 코드

Cross-lingual Editing in Multilingual Language Models

https://github.com/lins-lab/collabedit

공식 코드

CollabEdit: Towards Non-destructive Collaborative Knowledge Editing

https://github.com/liujf69/MMCL-Action

공식 코드

Multi-Modality Co-Learning for Efficient Skeleton-based Action Recognition

https://github.com/liujf69/icmew2024-track10

공식 코드

HDBN: A Novel Hybrid Dual-branch Network for Robust Skeleton-based Action Recognition

https://github.com/lizaowo/hpi-gcn

공식 코드

High-Performance Inference Graph Convolutional Networks for Skeleton-Based Action Recognition

https://github.com/lliutianc/roselora

공식 코드

RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning

https://github.com/llm-editing/HalluEditBench

공식 코드

Can Knowledge Editing Really Correct Hallucinations?

https://github.com/lqinfdim/editingevaluation

공식 코드

Should We Really Edit Language Models? On the Evaluation of Edited Language Models

https://github.com/lshiwjx/2s-AGCN

공식 코드

Skeleton-Based Action Recognition with Multi-Stream Adaptive Graph Convolutional Networks

https://github.com/lshiwjx/DSTA-Net

공식 코드

Decoupled Spatial-Temporal Attention Network for Skeleton-Based Action Recognition

https://github.com/lukashedegaard/continual-skeletons

공식 코드

Continual Spatio-Temporal Graph Convolutional Networks

https://github.com/machelreid/editpro

공식 코드

Learning to Model Editing Processes

https://github.com/maclong01/STEP-CATFormer

공식 코드

STEP CATFormer: Spatial-Temporal Effective Body-Part Cross Attention Transformer for Skeleton-based Action Recognition

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