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2D Classification

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코드

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

https://bitbucket.org/YanivShu/binary_weighted_networks_public

공식 코드

Exact Backpropagation in Binary Weighted Networks with Group Weight Transformations

https://bitbucket.org/bookcold/vandal_detection

공식 코드

Wikipedia Vandal Early Detection: from User Behavior to User Embedding

https://bitbucket.org/edge-team-leat/microai_public

공식 코드

Quantization and Deployment of Deep Neural Networks on Microcontrollers

https://bitbucket.org/gsudmlab/multiscale_iou

공식 코드

Multiscale IoU: A Metric for Evaluation of Salient Object Detection with Fine Structures

https://bitbucket.org/leoeaton/quase

공식 코드

QuaSE: Accurate Text Style Transfer under Quantifiable Guidance

https://bitbucket.org/st157585/emotion_transfer

공식 코드

Challenges in Emotion Style Transfer: An Exploration with a Lexical Substitution Pipeline

https://git.openi.org.cn/OpenPointCloud/PCSOD

공식 코드

Salient Object Detection for Point Clouds

https://gitee.com/HarveyYeung/FPNet-MindSpore.git

공식 코드

Frequency Perception Network for Camouflaged Object Detection

https://gitee.com/HarveyYeung/GLNet-TCYB2022-MindSpore.git

공식 코드

Global-and-Local Collaborative Learning for Co-Salient Object Detection

https://gitee.com/Lin-Qinwei/CIR-Net-MindSpore.git

공식 코드

CIR-Net: Cross-modality Interaction and Refinement for RGB-D Salient Object Detection

https://github.com/01yzzyu/wikiautogen

공식 코드

WikiAutoGen: Towards Multi-Modal Wikipedia-Style Article Generation

https://github.com/0nutation/speechgpt

공식 코드

SpeechGPT-Gen: Scaling Chain-of-Information Speech Generation

https://github.com/1170300714/w2n_wsod

공식 코드

W2N:Switching From Weak Supervision to Noisy Supervision for Object Detection

https://github.com/16337093/PnP-FSOD

공식 코드

Instant Response Few-shot Object Detection with Meta Strategy and Explicit Localization Inference

https://github.com/1adrianb/binary-networks-pytorch

공식 코드

XNOR-Net++: Improved Binary Neural Networks

https://github.com/1e12leon/uemm-air

공식 코드

UEMM-Air: A Synthetic Multi-modal Dataset for Unmanned Aerial Vehicle Object Detection

https://github.com/1j4j1230/fight_fire_with_fire

공식 코드

Fight Fire with Fire: Combating Adversarial Patch Attacks using Pattern-randomized Defensive Patches

https://github.com/1ssb/UOD

공식 코드

Believing is Seeing: Unobserved Object Detection using Generative Models

https://github.com/1wuming/WalnutData

공식 코드

WalnutData: A UAV Remote Sensing Dataset of Green Walnuts and Model Evaluation

https://github.com/2-Chae/A-NDFT

공식 코드

Training Domain-invariant Object Detector Faster with Feature Replay and Slow Learner

https://github.com/20000yshust/swarm

공식 코드

Not All Prompts Are Secure: A Switchable Backdoor Attack Against Pre-trained Vision Transformers

https://github.com/2019chengong/offline_rl_poisoner

공식 코드

BAFFLE: Hiding Backdoors in Offline Reinforcement Learning Datasets

https://github.com/2771096196/RepAct

공식 코드

RepAct: The Re-parameterizable Adaptive Activation Function

https://github.com/343gltysprk/ovow

공식 코드

From Open Vocabulary to Open World: Teaching Vision Language Models to Detect Novel Objects

https://github.com/360cvgroup/fg-clip

공식 코드

FG-CLIP: Fine-Grained Visual and Textual Alignment

https://github.com/3DAgentWorld/Toolkit-for-Prompt-Compression

공식 코드

An Empirical Study on Prompt Compression for Large Language Models

https://github.com/3dperceptionlab/unrealrox

공식 코드

UnrealROX: An eXtremely Photorealistic Virtual Reality Environment for Robotics Simulations and Synthetic Data Generation

https://github.com/3dperceptionlab/unrealrox-plus

공식 코드

UnrealROX+: An Improved Tool for Acquiring Synthetic Data from Virtual 3D Environments

https://github.com/41enthusiast/ST-SACLF-ver1.1

공식 코드

ST-SACLF: Style Transfer Informed Self-Attention Classifier for Bias-Aware Painting Classification

https://github.com/41enthusiast/st-saclf

공식 코드

Tackling Data Bias in Painting Classification with Style Transfer

https://github.com/42shawn/causal-dfq

공식 코드

Causal-DFQ: Causality Guided Data-free Network Quantization

https://github.com/4dvlab/stcrowd

공식 코드

STCrowd: A Multimodal Dataset for Pedestrian Perception in Crowded Scenes

https://github.com/514flowey/jdet-cobb

공식 코드

Theoretically Achieving Continuous Representation of Oriented Bounding Boxes

https://github.com/51616/split-vae

공식 코드

An Explicit Local and Global Representation Disentanglement Framework with Applications in Deep Clustering and Unsupervised Object Detection

https://github.com/5chen/mixnet

공식 코드

MixNet: Efficient Global Modeling for Ultra-High-Definition Image Restoration

https://github.com/6272code/6272-code

공식 코드

Restoring Images with Unknown Degradation Factors by Recurrent Use of a Multi-branch Network

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.