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코드

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

https://github.com/liyunfenglyf/uostrack

공식 코드

Underwater Object Tracker: UOSTrack for Marine Organism Grasping of Underwater Vehicles

https://github.com/liyunsheng13/dpp

공식 코드

Should All Proposals be Treated Equally in Object Detection?

https://github.com/liz66666/gpa3d

공식 코드

GPA-3D: Geometry-aware Prototype Alignment for Unsupervised Domain Adaptive 3D Object Detection from Point Clouds

https://github.com/lizhh268/shadowmaskformer

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ShadowMaskFormer: Mask Augmented Patch Embeddings for Shadow Removal

https://github.com/lizhuoling/voxelformer-public

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VoxelFormer: Bird's-Eye-View Feature Generation based on Dual-view Attention for Multi-view 3D Object Detection

https://github.com/lizixing23/AMBOKD

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Adaptive Modality Balanced Online Knowledge Distillation for Brain-Eye-Computer based Dim Object Detection

https://github.com/lizzy8587/castdet

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Toward Open Vocabulary Aerial Object Detection with CLIP-Activated Student-Teacher Learning

https://github.com/ljacksonpan/ratrack

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RaTrack: Moving Object Detection and Tracking with 4D Radar Point Cloud

https://github.com/lkeab/BCNet

공식 코드

Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers

https://github.com/lliuz/mixteacher

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MixTeacher: Mining Promising Labels with Mixed Scale Teacher for Semi-Supervised Object Detection

https://github.com/lluckyyh/vt-ada

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Vision Transformer-based Adversarial Domain Adaptation

https://github.com/lluisgomez/TextTopicNet

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TextTopicNet - Self-Supervised Learning of Visual Features Through Embedding Images on Semantic Text Spaces

https://github.com/lmb-freiburg/locov

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Localized Vision-Language Matching for Open-vocabulary Object Detection

https://github.com/lmb-freiburg/ovqa

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Open-ended VQA benchmarking of Vision-Language models by exploiting Classification datasets and their semantic hierarchy

https://github.com/lmd0311/hermes

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HERMES: A Unified Self-Driving World Model for Simultaneous 3D Scene Understanding and Generation

https://github.com/lmhieu612/SID

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Shadow Removal via Shadow Image Decomposition

https://github.com/lmmh058/fsatfusion

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FSATFusion: Frequency-Spatial Attention Transformer for Infrared and Visible Image Fusion

https://github.com/lmmmeng/overlock

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OverLoCK: An Overview-first-Look-Closely-next ConvNet with Context-Mixing Dynamic Kernels

https://github.com/lmmmeng/sparx

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SparX: A Sparse Cross-Layer Connection Mechanism for Hierarchical Vision Mamba and Transformer Networks

https://github.com/lmmmeng/transxnet

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TransXNet: Learning Both Global and Local Dynamics with a Dual Dynamic Token Mixer for Visual Recognition

https://github.com/lms-07/lgteun

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Local-Global Transformer Enhanced Unfolding Network for Pan-sharpening

https://github.com/logsanand/Monocular-depth-UAVimages

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Self-supervised monocular depth estimation from oblique UAV videos

https://github.com/loibo/stabilize_neural_networks

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To be or not to be stable, that is the question: understanding neural networks for inverse problems

https://github.com/loibo/tobeornottobestable

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To be or not to be stable, that is the question: understanding neural networks for inverse problems

https://github.com/loiccordone/object-detection-with-spiking-neural-networks

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Object Detection with Spiking Neural Networks on Automotive Event Data

https://github.com/lojzezust/pansr

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PanSR: An Object-Centric Mask Transformer for Panoptic Segmentation

https://github.com/lolipopshock/Detectron2_AL

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OLALA: Object-Level Active Learning for Efficient Document Layout Annotation

https://github.com/lonelyhope/dada

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Dual Adversarial Adaptation for Cross-Device Real-World Image Super-Resolution

https://github.com/long-username/DTDN-DTDN-Dual-task-De-raining-Network

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DTDN: Dual-task De-raining Network

https://github.com/longbai1006/surgical-vqla

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Surgical-VQLA: Transformer with Gated Vision-Language Embedding for Visual Question Localized-Answering in Robotic Surgery

https://github.com/longchencv/uodreview

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Underwater Object Detection in the Era of Artificial Intelligence: Current, Challenge, and Future

https://github.com/longkukuhi/armbench

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RoboLLM: Robotic Vision Tasks Grounded on Multimodal Large Language Models

https://github.com/lookdeep/ai-norms-2024

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Continuous Patient Monitoring with AI: Real-Time Analysis of Video in Hospital Care Settings

https://github.com/looooongchen/sortedap

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SortedAP: Rethinking evaluation metrics for instance segmentation

https://github.com/lorebianchi98/fg-clip

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Is CLIP the main roadblock for fine-grained open-world perception?

https://github.com/lorebianchi98/fg-ovd

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The devil is in the fine-grained details: Evaluating open-vocabulary object detectors for fine-grained understanding

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