https://github.com/gwenzhang/voxel-mamba
공식 코드Voxel Mamba: Group-Free State Space Models for Point Cloud based 3D Object Detection
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/gwxuan/tsp3d
공식 코드Text-guided Sparse Voxel Pruning for Efficient 3D Visual Grounding
https://github.com/gyauney/domain-specific-lexical-grounding
공식 코드Domain-Specific Lexical Grounding in Noisy Visual-Textual Documents
https://github.com/gyglim/personalized-highlights-dataset
공식 코드PHD-GIFs: Personalized Highlight Detection for Automatic GIF Creation
https://github.com/gyguo/pixeldistillation
공식 코드Pixel Distillation: A New Knowledge Distillation Scheme for Low-Resolution Image Recognition
https://github.com/gyhandy/3d-copy-paste
공식 코드3D Copy-Paste: Physically Plausible Object Insertion for Monocular 3D Detection
https://github.com/gyhandy/neural-sim-nerf
공식 코드https://github.com/gyhandy/text2image-for-detection
공식 코드Beyond Generation: Harnessing Text to Image Models for Object Detection and Segmentation
https://github.com/gyxxyg/vtg-llm
공식 코드VTG-LLM: Integrating Timestamp Knowledge into Video LLMs for Enhanced Video Temporal Grounding
https://github.com/gyyang23/afpn
공식 코드AFPN: Asymptotic Feature Pyramid Network for Object Detection
https://github.com/h-deep/trans-svsr
공식 코드A New Dataset and Transformer for Stereoscopic Video Super-Resolution
https://github.com/h751410234/datr
공식 코드https://github.com/haarburger/multi-scale-curriculum
공식 코드Multi Scale Curriculum CNN for Context-Aware Breast MRI Malignancy Classification
https://github.com/hadi-ghnd/accidentdetection
공식 코드Real-Time Accident Detection in Traffic Surveillance Using Deep Learning
https://github.com/hadi-ghnd/scrap-classification
공식 코드https://github.com/hadipardis/svc
공식 코드https://github.com/haibao-yu/ffnet-vic3d
공식 코드Vehicle-Infrastructure Cooperative 3D Object Detection via Feature Flow Prediction
https://github.com/hailanyi/cpd
공식 코드Commonsense Prototype for Outdoor Unsupervised 3D Object Detection
https://github.com/hailanyi/virconv
공식 코드Virtual Sparse Convolution for Multimodal 3D Object Detection
https://github.com/haiyang-w/cagroup3d
공식 코드CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds
https://github.com/haiyang-w/dsvt
공식 코드https://github.com/haiyang-w/rbgnet
공식 코드https://github.com/haiyang-w/unitr
공식 코드UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View Representation
https://github.com/hama-dl-dev/sesame
공식 코드SeSame: Simple, Easy 3D Object Detection with Point-Wise Semantics
https://github.com/hamarh/HMNet_pth
공식 코드Hierarchical Neural Memory Network for Low Latency Event Processing
https://github.com/hamperdredes/sood
공식 코드https://github.com/hamzafer/image-deblurring
공식 코드Efficient Transformer for High Resolution Image Motion Deblurring
https://github.com/hananshafi/llmblueprint
공식 코드LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts
https://github.com/hanchaa/meformer
공식 코드https://github.com/hancyran/RepSurf
공식 코드https://github.com/hancyran/lidar-diffusion
공식 코드Towards Realistic Scene Generation with LiDAR Diffusion Models
https://github.com/haneul-yoo/csrt
공식 코드Code-Switching Red-Teaming: LLM Evaluation for Safety and Multilingual Understanding
https://github.com/hangg7/deformable-kernels/
공식 코드Deformable Kernels: Adapting Effective Receptive Fields for Object Deformation
https://github.com/hangxu-cv/cvpr24acm
공식 코드Rethinking Boundary Discontinuity Problem for Oriented Object Detection
https://github.com/hanktseng131415go/ramem
공식 코드https://github.com/hanlinwu/sadn
공식 코드Scale-Aware Dynamic Network for Continuous-Scale Super-Resolution
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.