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2D Classification
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/sinamalakouti/CDDMSL
공식 코드Semi-Supervised Domain Generalization for Object Detection via Language-Guided Feature Alignment
https://github.com/sinatayebati/radial_mae
공식 코드https://github.com/sindish/unitedwelearn
공식 코드United We Learn Better: Harvesting Learning Improvements From Class Hierarchies Across Tasks
https://github.com/sinhala-nlp/nsina
공식 코드https://github.com/sinhala-nlp/sinhala-headline-generation
공식 코드https://github.com/sinhala-nlp/sinhala-news-category-prediction
공식 코드https://github.com/sinhala-nlp/sinhala-news-media-identification
공식 코드https://github.com/sinmdm/sinmdm
공식 코드https://github.com/sisinflab/adversarial-recommender-systems-survey
공식 코드https://github.com/sisl-uri/arch_backdoor_llm
공식 코드Exploiting the Vulnerability of Large Language Models via Defense-Aware Architectural Backdoor
https://github.com/sisl-uri/noiseattack
공식 코드NoiseAttack: An Evasive Sample-Specific Multi-Targeted Backdoor Attack Through White Gaussian Noise
https://github.com/sisl/visionbasedaircraftdaa
공식 코드AVOIDDS: Aircraft Vision-based Intruder Detection Dataset and Simulator
https://github.com/sissiw/mutualformer
공식 코드MutualFormer: Multi-Modality Representation Learning via Cross-Diffusion Attention
https://github.com/siyueyu/SCWSSOD
공식 코드Structure-Consistent Weakly Supervised Salient Object Detection with Local Saliency Coherence
https://github.com/siyueyu/dcfm
공식 코드Democracy Does Matter: Comprehensive Feature Mining for Co-Salient Object Detection
https://github.com/siyuhuang/quantart
공식 코드QuantArt: Quantizing Image Style Transfer Towards High Visual Fidelity
https://github.com/sjames40/ugodit
공식 코드UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weights
https://github.com/sjtuplayer/compositional_neural_painter
공식 코드Stroke-based Neural Painting and Stylization with Dynamically Predicted Painting Region
https://github.com/skmhrk1209/VSRD
공식 코드VSRD: Instance-Aware Volumetric Silhouette Rendering for Weakly Supervised 3D Object Detection
https://github.com/skoffas/going-in-style
공식 코드Going In Style: Audio Backdoors Through Stylistic Transformations
https://github.com/skokec/DAU-ConvNet
공식 코드Spatially-Adaptive Filter Units for Compact and Efficient Deep Neural Networks
https://github.com/skokec/DAU-ConvNet-TF
공식 코드Spatially-Adaptive Filter Units for Compact and Efficient Deep Neural Networks
https://github.com/skokec/DAU-ConvNet-caffe
공식 코드Spatially-Adaptive Filter Units for Compact and Efficient Deep Neural Networks
https://github.com/skoltech-nlp/detox
공식 코드https://github.com/skoltech-nlp/formality
공식 코드Detecting Text Formality: A Study of Text Classification Approaches
https://github.com/skoltech-nlp/multilingual_detox
공식 코드Exploring Cross-lingual Textual Style Transfer with Large Multilingual Language Models
https://github.com/skoltech-nlp/rudetoxifier
공식 코드Methods for Detoxification of Texts for the Russian Language
https://github.com/skoltech-nlp/sgdd-tst
공식 코드Studying the role of named entities for content preservation in text style transfer
https://github.com/sky77764/pa-aug.pytorch
공식 코드Part-Aware Data Augmentation for 3D Object Detection in Point Cloud
https://github.com/skyhehe123/msf
공식 코드MSF: Motion-guided Sequential Fusion for Efficient 3D Object Detection from Point Cloud Sequences
https://github.com/skyhehe123/voxset
공식 코드Voxel Set Transformer: A Set-to-Set Approach to 3D Object Detection from Point Clouds
https://github.com/skyoux/SemAIM
공식 코드Semantic-Aware Autoregressive Image Modeling for Visual Representation Learning
https://github.com/slanglab/IndiaPoliceEvents
공식 코드https://github.com/sldgroup/mobilevig
공식 코드MobileViG: Graph-Based Sparse Attention for Mobile Vision Applications
https://github.com/sldgroup/mobilevigv2
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.