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평가표

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보존된 평가 기록

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코드

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

https://github.com/donglao/mindelay

공식 코드

Minimum Delay Object Detection From Video

https://github.com/dongnana777/bridging-non-co-occurrence

공식 코드

Bridging Non Co-occurrence with Unlabeled In-the-wild Data for Incremental Object Detection

https://github.com/dongsky/mr-gdino

공식 코드

MR-GDINO: Efficient Open-World Continual Object Detection

https://github.com/dongw22/oath

공식 코드

Retinex-guided Histogram Transformer for Mask-free Shadow Removal

https://github.com/dongwoohhh/GS-Blur

공식 코드

GS-Blur: A 3D Scene-Based Dataset for Realistic Image Deblurring

https://github.com/donkeymouse/thermalchameleon

공식 코드

Thermal Chameleon: Task-Adaptive Tone-mapping for Radiometric Thermal-Infrared images

https://github.com/dop0/dvpe

공식 코드

DVPE: Divided View Position Embedding for Multi-View 3D Object Detection

https://github.com/doranlyong/spanetv2-official

공식 코드

Spectral-Adaptive Modulation Networks for Visual Perception

https://github.com/dorarad/gansformer

공식 코드

Generative Adversarial Transformers

https://github.com/dotori-hj/digit

공식 코드

DiGIT: Multi-Dilated Gated Encoder and Central-Adjacent Region Integrated Decoder for Temporal Action Detection Transformer

https://github.com/dotori-hj/te-tad

공식 코드

TE-TAD: Towards Full End-to-End Temporal Action Detection via Time-Aligned Coordinate Expression

https://github.com/douglasrizzo/JINT2020-ball-detection

공식 코드

Detecting soccer balls with reduced neural networks: a comparison of multiple architectures under constrained hardware scenarios

https://github.com/dpaul06/VideoLights

공식 코드

VideoLights: Feature Refinement and Cross-Task Alignment Transformer for Joint Video Highlight Detection and Moment Retrieval

https://github.com/dr-lingxiao/ag-man

공식 코드

Attribute-Guided Multi-Level Attention Network for Fine-Grained Fashion Retrieval

https://github.com/dragonlee258079/DMT

공식 코드

Discriminative Co-Saliency and Background Mining Transformer for Co-Salient Object Detection

https://github.com/dragonlzm/EZSD

공식 코드

Efficient Feature Distillation for Zero-shot Annotation Object Detection

https://github.com/dragonlzm/ezad

공식 코드

Efficient Feature Distillation for Zero-shot Annotation Object Detection

https://github.com/dreamscene4d/dreamscene4d

공식 코드

DreamScene4D: Dynamic Multi-Object Scene Generation from Monocular Videos

https://github.com/dreossi/analyzeNN

공식 코드

Counterexample-Guided Data Augmentation

https://github.com/drilistbox/3dppe

공식 코드

3DPPE: 3D Point Positional Encoding for Multi-Camera 3D Object Detection Transformers

https://github.com/drl-casia/mvm3d

공식 코드

MVM3Det: A Novel Method for Multi-view Monocular 3D Detection

https://github.com/drlxj/camdiff

공식 코드

CamDiff: Camouflage Image Augmentation via Diffusion Model

https://github.com/drowsymon/rmformer

공식 코드

Recurrent Multi-scale Transformer for High-Resolution Salient Object Detection

https://github.com/drscotthawley/SPNet

공식 코드

ConvNets for Counting: Object Detection of Transient Phenomena in Steelpan Drums

https://github.com/dschinagl/occam

공식 코드

OccAM's Laser: Occlusion-based Attribution Maps for 3D Object Detectors on LiDAR Data

https://github.com/dsciitism/segpc-2021

공식 코드

Transformer Assisted Convolutional Network for Cell Instance Segmentation

https://github.com/dslisleedh/ESC

공식 코드

Emulating Self-attention with Convolution for Efficient Image Super-Resolution

https://github.com/dslisleedh/IGConv

공식 코드

Implicit Grid Convolution for Multi-Scale Image Super-Resolution

https://github.com/dslisleedh/PLKSR

공식 코드

Partial Large Kernel CNNs for Efficient Super-Resolution

https://github.com/dsriaditya999/rgbxfusion

공식 코드

RGB-X Object Detection via Scene-Specific Fusion Modules

https://github.com/dsshim0125/SwinDepth

공식 코드

SwinDepth: Unsupervised Depth Estimation using Monocular Sequences via Swin Transformer and Densely Cascaded Network

https://github.com/dsshim0125/grmc

공식 코드

Learning a Geometric Representation for Data-Efficient Depth Estimation via Gradient Field and Contrastive Loss

https://github.com/dsx0511/3dmotformer

공식 코드

3DMOTFormer: Graph Transformer for Online 3D Multi-Object Tracking

https://github.com/duan-song/SATNet

공식 코드

Lightweight RGB-D Salient Object Detection from a Speed-Accuracy Tradeoff Perspective

https://github.com/duanlab123/curvpnp

공식 코드

CurvPnP: Plug-and-play Blind Image Restoration with Deep Curvature Denoiser

https://github.com/duckduckpig/regression_blur

공식 코드

Estimation of motion blur kernel parameters using regression convolutional neural networks

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