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Semantic Compression
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/CrashedBboy/SGGIC
공식 코드https://github.com/codefuse-ai/rodimus
공식 코드Rodimus*: Breaking the Accuracy-Efficiency Trade-Off with Efficient Attentions
https://github.com/eddy6081/pen
공식 코드https://github.com/jqtangust/IUF
공식 코드An Incremental Unified Framework for Small Defect Inspection
https://github.com/landiff/landiff
공식 코드The Best of Both Worlds: Integrating Language Models and Diffusion Models for Video Generation
https://github.com/lcysyzxdxc/misc
공식 코드MISC: Ultra-low Bitrate Image Semantic Compression Driven by Large Multimodal Model
https://github.com/protim1191/glodismo_classifier
공식 코드Compressed learning based onboard semantic compression for remote sensing platforms
https://github.com/skyd-semantic/drgo-semcom
공식 코드Distortion Resilience for Goal-Oriented Semantic Communication
https://github.com/slz-ai/hfedms
공식 코드HFedMS: Heterogeneous Federated Learning with Memorable Data Semantics in Industrial Metaverse
https://github.com/sustcsonglin/flash-linear-attention
공식 코드Rodimus*: Breaking the Accuracy-Efficiency Trade-Off with Efficient Attentions
https://github.com/tianyuan168326/videosemanticcompression-pytorch
공식 코드SMC++: Masked Learning of Unsupervised Video Semantic Compression
https://github.com/zacharynovack/lead-ae
공식 코드https://github.com/srgrace/contextual-compression
Extending Context Window of Large Language Models via Semantic Compression
https://github.com/tokkiwa/MISC-colab
MISC: Ultra-low Bitrate Image Semantic Compression Driven by Large Multimodal Model
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.