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Dataset Generation

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The task involves enhancing the training of target application (e.g. autonomous driving systems) by generating datasets of diverse and critical elements (e.g. traffic scenarios). Traditional methods rely on expensive and limited datasets, which often fail to capture rare but essential situations that can pose risks during testing.

코드

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

https://github.com/mshenoda/diffugen

공식 코드

DiffuGen: Adaptable Approach for Generating Labeled Image Datasets using Stable Diffusion Models

https://github.com/muhayyuddin/vlas

공식 코드

Vision Language Action Models in Robotic Manipulation: A Systematic Review

https://github.com/naivete5656/mdpafof

공식 코드

Mitosis Detection from Partial Annotation by Dataset Generation via Frame-Order Flipping

https://github.com/nasa-jpl/guiss

공식 코드

Icy Moon Surface Simulation and Stereo Depth Estimation for Sampling Autonomy

https://github.com/nehamjain10/trudgcr

공식 코드

Towards Realistic Underwater Dataset Generation and Color Restoration

https://github.com/neulab/prompt2model

공식 코드

Prompt2Model: Generating Deployable Models from Natural Language Instructions

https://github.com/ngzhili/syntable

공식 코드

SynTable: A Synthetic Data Generation Pipeline for Unseen Object Amodal Instance Segmentation of Cluttered Tabletop Scenes

https://github.com/nibir088/irrmap

공식 코드

IrrMap: A Large-Scale Comprehensive Dataset for Irrigation Method Mapping

https://github.com/openbmb/rageval

공식 코드

RAGEval: Scenario Specific RAG Evaluation Dataset Generation Framework

https://github.com/pantheon5100/pid_diffusion

공식 코드

Physics Informed Distillation for Diffusion Models

https://github.com/quaife/FDV_Data

공식 코드

Fire Dynamic Vision: Image Segmentation and Tracking for Multi-Scale Fire and Plume Behavior

https://github.com/retrieva/japagen

공식 코드

JAPAGEN: Efficient Few/Zero-shot Learning via Japanese Training Dataset Generation with LLM

https://github.com/richardmarcus/synth-it-like-kitti

공식 코드

Synth It Like KITTI: Synthetic Data Generation for Object Detection in Driving Scenarios

https://github.com/ridiculouz/llmaaa

공식 코드

LLMaAA: Making Large Language Models as Active Annotators

https://github.com/rwth-irt/deepnlosdetection

공식 코드

Learning-based NLOS Detection and Uncertainty Prediction of GNSS Observations with Transformer-Enhanced LSTM Network

https://github.com/sanoscience/simuscope

공식 코드

SimuScope: Realistic Endoscopic Synthetic Dataset Generation through Surgical Simulation and Diffusion Models

https://github.com/shahrukhqasim/TIES-2.0

공식 코드

Rethinking Table Recognition using Graph Neural Networks

https://github.com/showlab/datasetdm

공식 코드

DatasetDM: Synthesizing Data with Perception Annotations Using Diffusion Models

https://github.com/sinop97/drive_sim_road_generation

공식 코드

Semantic Segmentation for Autonomous Driving: Model Evaluation, Dataset Generation, Perspective Comparison, and Real-Time Capability

https://github.com/spatialaudiotools/sofamyroom

공식 코드

SofaMyRoom: a fast and multiplatform "shoebox" room simulator for binaural room impulse response dataset generation

https://github.com/takomc/amp

공식 코드

Automated Multi-level Preference for MLLMs

https://github.com/tecsar-uncc/adg-pose

공식 코드

ADG-Pose: Automated Dataset Generation for Real-World Human Pose Estimation

https://github.com/tio-ikim/cellvit-plus-plus

공식 코드

CellViT++: Energy-Efficient and Adaptive Cell Segmentation and Classification Using Foundation Models

https://github.com/tkn-tub/nn_molecular_communications

공식 코드

Communicating Smartly in the Molecular Domain: Neural Networks in the Internet of Bio-Nano Things

https://github.com/tumaer/jax-sph

공식 코드

JAX-SPH: A Differentiable Smoothed Particle Hydrodynamics Framework

https://github.com/ulrs0/MA-PO

공식 코드

The Fellowship of the LLMs: Multi-Agent Workflows for Synthetic Preference Optimization Dataset Generation

https://github.com/unifyid-labs/DeepGenStruct-Notebooks

공식 코드

Fonts-2-Handwriting: A Seed-Augment-Train framework for universal digit classification

https://github.com/vinairesearch/dataset-diffusion

공식 코드

Dataset Diffusion: Diffusion-based Synthetic Dataset Generation for Pixel-Level Semantic Segmentation

https://github.com/vincentkoc/tiny_qa_benchmark_pp

공식 코드

Tiny QA Benchmark++: Ultra-Lightweight, Synthetic Multilingual Dataset Generation & Smoke-Tests for Continuous LLM Evaluation

https://github.com/vint-1/chipdiffusion

공식 코드

Chip Placement with Diffusion Models

https://github.com/xin-wang18/MISE

공식 코드

Cognition Chain for Explainable Psychological Stress Detection on Social Media

https://github.com/y0mingzhang/diffuse-distributions

공식 코드

Forcing Diffuse Distributions out of Language Models

https://github.com/y0mingzhang/diffuse-probabilities

공식 코드

Forcing Diffuse Distributions out of Language Models

https://github.com/yu-billie/kocosa_sarcasm_detection

공식 코드

KoCoSa: Korean Context-aware Sarcasm Detection Dataset

https://github.com/yu-jingrui/NToP

공식 코드

NToP: NeRF-Powered Large-scale Dataset Generation for 2D and 3D Human Pose Estimation in Top-View Fisheye Images

https://github.com/zhaoyuzhi/icm-assistant

공식 코드

ICM-Assistant: Instruction-tuning Multimodal Large Language Models for Rule-based Explainable Image Content Moderation

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