https://github.com/lmmh058/fsatfusion
공식 코드FSATFusion: Frequency-Spatial Attention Transformer for Infrared and Visible Image Fusion
Papers with Code 아카이브
Object Detection
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/lmmmeng/overlock
공식 코드OverLoCK: An Overview-first-Look-Closely-next ConvNet with Context-Mixing Dynamic Kernels
https://github.com/lmmmeng/sparx
공식 코드https://github.com/lmmmeng/transxnet
공식 코드https://github.com/logsanand/Monocular-depth-UAVimages
공식 코드Self-supervised monocular depth estimation from oblique UAV videos
https://github.com/loiccordone/object-detection-with-spiking-neural-networks
공식 코드Object Detection with Spiking Neural Networks on Automotive Event Data
https://github.com/lojzezust/pansr
공식 코드PanSR: An Object-Centric Mask Transformer for Panoptic Segmentation
https://github.com/lolipopshock/Detectron2_AL
공식 코드OLALA: Object-Level Active Learning for Efficient Document Layout Annotation
https://github.com/long-username/DTDN-DTDN-Dual-task-De-raining-Network
공식 코드https://github.com/longbai1006/surgical-vqla
공식 코드https://github.com/longchencv/uodreview
공식 코드Underwater Object Detection in the Era of Artificial Intelligence: Current, Challenge, and Future
https://github.com/longkukuhi/armbench
공식 코드RoboLLM: Robotic Vision Tasks Grounded on Multimodal Large Language Models
https://github.com/lookdeep/ai-norms-2024
공식 코드Continuous Patient Monitoring with AI: Real-Time Analysis of Video in Hospital Care Settings
https://github.com/looooongchen/sortedap
공식 코드SortedAP: Rethinking evaluation metrics for instance segmentation
https://github.com/lorebianchi98/fg-clip
공식 코드Is CLIP the main roadblock for fine-grained open-world perception?
https://github.com/lorebianchi98/fg-ovd
공식 코드https://github.com/lovelyqian/CDFSOD-benchmark
공식 코드Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object Detector
https://github.com/lovelyqian/ntire2025_cdfsod
공식 코드NTIRE 2025 Challenge on Cross-Domain Few-Shot Object Detection: Methods and Results
https://github.com/lowlevelai/glare
공식 코드GLARE: Low Light Image Enhancement via Generative Latent Feature based Codebook Retrieval
https://github.com/ltzovo/damamba
공식 코드DAMamba: Vision State Space Model with Dynamic Adaptive Scan
https://github.com/luckybird1994/hqsod
공식 코드https://github.com/luckybird1994/mmcpf
공식 코드https://github.com/luckybird1994/samcod
공식 코드Can SAM Segment Anything? When SAM Meets Camouflaged Object Detection
https://github.com/luigisigillo/shipinsight
공식 코드Ship in Sight: Diffusion Models for Ship-Image Super Resolution
https://github.com/luisfelipewb/potato
공식 코드PoTATO: A Dataset for Analyzing Polarimetric Traces of Afloat Trash Objects
https://github.com/luiszeni/Boosted-OICR
공식 코드Distilling Knowledge from Refinement in Multiple Instance Detection Networks
https://github.com/lukasc-ch/CBinfer
공식 코드https://github.com/lukazso/kpbms-pvdn
공식 코드https://github.com/luluho1208/diffusion-ss3d
공식 코드Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object Detection
https://github.com/luo-z13/pointobb
공식 코드PointOBB: Learning Oriented Object Detection via Single Point Supervision
https://github.com/luo3300612/image-captioning-DLCT
공식 코드https://github.com/luogen1996/oneteacher
공식 코드Towards End-to-end Semi-supervised Learning for One-stage Object Detection
https://github.com/luoyadan/crb-active-3ddet
공식 코드Exploring Active 3D Object Detection from a Generalization Perspective
https://github.com/luoyan407/gradient_adjustment
공식 코드https://github.com/luping-liu/detector-guidance
공식 코드https://github.com/lutao2021/pidray
공식 코드PIDray: A Large-scale X-ray Benchmark for Real-World Prohibited Item Detection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.