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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/lanlan96/arm3d

공식 코드

ARM3D: Attention-based relation module for indoor 3D object detection

https://github.com/laoyangui/dlsn

공식 코드

Global Learnable Attention for Single Image Super-Resolution

https://github.com/laprf/hrssd

공식 코드

Hyperspectral Remote Sensing Images Salient Object Detection: The First Benchmark Dataset and Baseline

https://github.com/laprf/smn

공식 코드

Spectrum-driven Mixed-frequency Network for Hyperspectral Salient Object Detection

https://github.com/laprf/spsd

공식 코드

Spectrum-oriented Point-supervised Saliency Detector for Hyperspectral Images

https://github.com/larsOhne/pvdn

공식 코드

Provident Vehicle Detection at Night: The PVDN Dataset

https://github.com/larskreuzberg/4d-stop

공식 코드

4D-StOP: Panoptic Segmentation of 4D LiDAR using Spatio-temporal Object Proposal Generation and Aggregation

https://github.com/lartpang/HDFNet

공식 코드

Hierarchical Dynamic Filtering Network for RGB-D Salient Object Detection

https://github.com/lartpang/MINet

공식 코드

Multi-scale Interactive Network for Salient Object Detection

https://github.com/lartpang/caver

공식 코드

CAVER: Cross-Modal View-Mixed Transformer for Bi-Modal Salient Object Detection

https://github.com/lartpang/comptr

공식 코드

ComPtr: Towards Diverse Bi-source Dense Prediction Tasks via A Simple yet General Complementary Transformer

https://github.com/lartpang/ovcamo

공식 코드

Open-Vocabulary Camouflaged Object Segmentation

https://github.com/lartpang/zoomnet

공식 코드

Zoom In and Out: A Mixed-scale Triplet Network for Camouflaged Object Detection

https://github.com/lartpang/zoomnext

공식 코드

ZoomNeXt: A Unified Collaborative Pyramid Network for Camouflaged Object Detection

https://github.com/laughtervv/SGPN

공식 코드

SGPN: Similarity Group Proposal Network for 3D Point Cloud Instance Segmentation

https://github.com/launchnlp/ManyICLBench

공식 코드

Retrieval or Global Context Understanding? On Many-Shot In-Context Learning for Long-Context Evaluation

https://github.com/laurimi/ddcrp-gibbs

공식 코드

Object proposal generation applying the distance dependent Chinese restaurant process

https://github.com/layneh/greenmim

공식 코드

Green Hierarchical Vision Transformer for Masked Image Modeling

https://github.com/lbc12345/sed

공식 코드

SeD: Semantic-Aware Discriminator for Image Super-Resolution

https://github.com/lbktrinh/DRU

공식 코드

Dynamic Retraining-Updating Mean Teacher for Source-Free Object Detection

https://github.com/lc012463/tanet

공식 코드

TANet: Transformer-based Asymmetric Network for RGB-D Salient Object Detection

https://github.com/lchen001/hapi

공식 코드

HAPI: A Large-scale Longitudinal Dataset of Commercial ML API Predictions

https://github.com/ldkong1205/Robo3D

공식 코드

Robo3D: Towards Robust and Reliable 3D Perception against Corruptions

https://github.com/ldtho/pifenet

공식 코드

Accurate and Real-time 3D Pedestrian Detection Using an Efficient Attentive Pillar Network

https://github.com/leaplabthu/agent-attention

공식 코드

Agent Attention: On the Integration of Softmax and Linear Attention

https://github.com/leaplabthu/dat

공식 코드

Vision Transformer with Deformable Attention

https://github.com/leaplabthu/deep-incubation

공식 코드

Deep Incubation: Training Large Models by Divide-and-Conquering

https://github.com/leaplabthu/dynamic_perceiver

공식 코드

Dynamic Perceiver for Efficient Visual Recognition

https://github.com/leaplabthu/lasnet

공식 코드

Latency-aware Spatial-wise Dynamic Networks

https://github.com/leaplabthu/model-assembling

공식 코드

Deep Incubation: Training Large Models by Divide-and-Conquering

https://github.com/leaplabthu/rank-detr

공식 코드

Rank-DETR for High Quality Object Detection

https://github.com/learninghx/tad-sr

공식 코드

One Step Diffusion-based Super-Resolution with Time-Aware Distillation

https://github.com/led-666/ttrd3

공식 코드

TTRD3: Texture Transfer Residual Denoising Dual Diffusion Model for Remote Sensing Image Super-Resolution

https://github.com/leeheewon-01/yolostratifiedkfold

공식 코드

Improving the performance of object detection by preserving label distribution

https://github.com/leenamx/ge-fsod

공식 코드

Generalization-Enhanced Few-Shot Object Detection in Remote Sensing

https://github.com/lefteyex/u-decn

공식 코드

U-DECN: End-to-End Underwater Object Detection ConvNet with Improved DeNoising Training

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