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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/sunjiahao1999/spformer

공식 코드

Superpoint Transformer for 3D Scene Instance Segmentation

https://github.com/sunlab-osu/covid-faq

공식 코드

COUGH: A Challenge Dataset and Models for COVID-19 FAQ Retrieval

https://github.com/sunny2109/mobilesr-ntire2022

공식 코드

ShuffleMixer: An Efficient ConvNet for Image Super-Resolution

https://github.com/sunny2109/safmn

공식 코드

Spatially-Adaptive Feature Modulation for Efficient Image Super-Resolution

https://github.com/sunpeng1996/DSA2F

공식 코드

Deep RGB-D Saliency Detection with Depth-Sensitive Attention and Automatic Multi-Modal Fusion

https://github.com/sunshenggu/xc_eval_pcdet

공식 코드

XC: Exploring Quantitative Use Cases for Explanations in 3D Object Detection

https://github.com/sunsmarterjie/SDL-Skeleton

공식 코드

Adaptive Linear Span Network for Object Skeleton Detection

https://github.com/sunsmarterjie/itpn

공식 코드

Fast-iTPN: Integrally Pre-Trained Transformer Pyramid Network with Token Migration

https://github.com/sunwj/CAR

공식 코드

Learned Image Downscaling for Upscaling using Content Adaptive Resampler

https://github.com/suojiashun/hit-uav-infrared-thermal-dataset

공식 코드

HIT-UAV: A high-altitude infrared thermal dataset for Unmanned Aerial Vehicle-based object detection

https://github.com/superkenvery/autolut

공식 코드

AutoLUT: LUT-Based Image Super-Resolution with Automatic Sampling and Adaptive Residual Learning

https://github.com/supermhp/gupnet

공식 코드

Geometry Uncertainty Projection Network for Monocular 3D Object Detection

https://github.com/supermhp/gupnet_plus

공식 코드

GUPNet++: Geometry Uncertainty Propagation Network for Monocular 3D Object Detection

https://github.com/supernlogn/squeezeDetTL

공식 코드

A Framework of Transfer Learning in Object Detection for Embedded Systems

https://github.com/superstar1225/DensePose_from_WiFi

공식 코드

DensePose From WiFi

https://github.com/supersupercong/uhdformer

공식 코드

Correlation Matching Transformation Transformers for UHD Image Restoration

https://github.com/superz678/mg-had

공식 코드

Multi-Granularity Hand Action Detection

https://github.com/supratikbanerjee/SubPixel-BackProjection_SuperResolution

공식 코드

Sub-Pixel Back-Projection Network For Lightweight Single Image Super-Resolution

https://github.com/suprosanna/relationformer

공식 코드

Relationformer: A Unified Framework for Image-to-Graph Generation

https://github.com/surajkothawade/talisman

공식 코드

TALISMAN: Targeted Active Learning for Object Detection with Rare Classes and Slices using Submodular Mutual Information

https://github.com/surrey-uplab/recognize-any-regions

공식 코드

Recognize Any Regions

https://github.com/sustainlab-group/geography-aware-ssl

공식 코드

Geography-Aware Self-Supervised Learning

https://github.com/sustainlab-group/is-count

공식 코드

IS-COUNT: Large-scale Object Counting from Satellite Images with Covariate-based Importance Sampling

https://github.com/sustech-isus/sustechgan

공식 코드

SUSTechGAN: Image Generation for Object Detection in Adverse Conditions of Autonomous Driving

https://github.com/suyukun666/UFO

공식 코드

A Unified Transformer Framework for Group-based Segmentation: Co-Segmentation, Co-Saliency Detection and Video Salient Object Detection

https://github.com/svip-lab/AS-MLP

공식 코드

AS-MLP: An Axial Shifted MLP Architecture for Vision

https://github.com/swamiviv/CLASP

공식 코드

Semantic uncertainty intervals for disentangled latent spaces

https://github.com/sweta20/Detecting-Cyberbullying-Across-SMPs

공식 코드

Deep Learning for Detecting Cyberbullying Across Multiple Social Media Platforms

https://github.com/swz30/MPRNet

공식 코드

MPRNet: Multi-Path Residual Network for Lightweight Image Super Resolution

https://github.com/swz30/restormer

공식 코드

Restormer: Efficient Transformer for High-Resolution Image Restoration

https://github.com/sxjyjay/msmdfusion

공식 코드

MSMDFusion: Fusing LiDAR and Camera at Multiple Scales with Multi-Depth Seeds for 3D Object Detection

https://github.com/sxpro/rfsr

공식 코드

RFSR: Improving ISR Diffusion Models via Reward Feedback Learning

https://github.com/synsin0/effocc

공식 코드

EFFOcc: A Minimal Baseline for EFficient Fusion-based 3D Occupancy Network

https://github.com/synsin0/srcn3d

공식 코드

SRCN3D: Sparse R-CNN 3D for Compact Convolutional Multi-View 3D Object Detection and Tracking

https://github.com/syscv/cascade-detr

공식 코드

Cascade-DETR: Delving into High-Quality Universal Object Detection

https://github.com/syscv/lidar_snow_sim

공식 코드

LiDAR Snowfall Simulation for Robust 3D Object Detection

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