yolov5 — Ultralytics YOLOv5 in PyTorch for object detection, instance segmentation, classification, training, and export.
YOLOv5という物体検出アルゴリズムをPyTorchから他の言語に変換できるライブラリ。
物体検出
MLINFO COLLECTION
外観検査・欠陥検出
製品画像、顕微鏡画像、表面欠陥を対象に、分類・検出・セグメンテーションを選ぶための導線です。
関連する論文・実装
19 / 50ComfyUI-LTXVideo — LTX-Video Support for ComfyUI
医療画像分析で、深層學習モデルが実装されている問題に対する解決策を提示します。治療を導くために、批判的結果に影響を与える変化について特に重点が置かれています。
医療画像を分析し治療を導く
Which Agent's Skill Should Change? Group-Relative Credit Assignment for Evolving Multi-Agent Teams
Cooperative language-model agents can improve without weight updates by revising reusable skills, but only if a shared team reward is traced to the responsible agent and skill. Existing methods…
computer-vision
insightface — State-of-the-art 2D and 3D Face Analysis Project
このプロジェクトは２Ｄおよび３Ｄ顔の分析を実現するための基盤プロジェクトであり、最先端の技術を導入して顔の分析を実現します。
面量認証
SelectPFN: Amortized Bayesian Variable Selection for Sparse Nonlinear Regression with Prior-Data Fitted Networks
Tabular foundation models based on prior-data fitted networks (PFNs) predict on a new data set in a single forward pass, but they cannot report which inputs their predictions depend on. We propose…
nlp
Simplified Swarm Optimization for Surrogate-Assisted Reliability Design of Insulated-Gate Bipolar Transistor Power Modules Using an Open-Source Process Finite-Element Model
Process-induced warpage, ceramic stress and solder strain limit the reliability of insulated-gate bipolar transistor (IGBT) modules on direct-bonded copper (DBC) substrates. Surrogate-assisted design…
computer-vision
Omni-InteractScope: Benchmarking Proactive and Agentic Interaction in Continuous Omnimodal Streams
Omnimodal large language models (Omni-LLMs) are increasingly expected to assist users while observing continuous audiovisual streams. However, existing evaluations provide limited insight into how…
nlp
Skill^{infty}: Recursive Self-Improvement for Agent Skill Optimization
Recursive self-improvement (RSI), in which a system also improves the way it improves, is a long-standing aspiration on the path to AGI. Language agents increasingly store procedural knowledge in…
computer-vision
Co-Design Bench: Multimodal Collaborative Coding Evaluation for Agentic Models
Evaluating human-AI co-design requires testing whether coding agents can translate real users' multimodal requests into working application revisions. We introduce Co-Design Bench, a reference-free…
nlp
More Memory, Better Videos? A Controlled Study of Visual Memory in Long-Video Generation
Long-video generators increasingly retrieve past visual observations to prevent identity drift. The intuition is compelling: more access to history should make future video more consistent.
generative-ai
What Outcome RL Buys: Finishing, Reliability, Rarely Reach
Outcome RL raises pass@1 but not pass@k at large k (Yue et al., 2025). But every pass@1 is scored under a token budget.
computer-vision
Benchmarking Obstacle-Conditioned Safety in Household Robot Navigation
Safe household navigation requires robots to regulate clearance and speed according to what an obstacle is and how close it is, without unnecessary conservatism. Yet existing evaluations do not test…
deep-learning
RynnVLA-Latent: Scaling Robotic Manipulation Foundation Models with 3D-Grounded Latent Actions
Scaling vision-language-action (VLA) models is constrained by scarce action-labeled demonstrations and incompatible control spaces across robot embodiments. We present RynnVLA-Latent, a framework…
nlp
HuGe: Scaling Humanoid Generalist Vision-Language-Action Models with Egocentric Experience
Extending Vision-Language-Action models (VLAs) to humanoid robots requires coordinated whole-body control and diverse demonstrations that are costly to collect in real-world scenarios. Although…
nlp
Mycelium: A Meta-Study of Hallucination Detection Across Provenance, Typology, and Granularities
Hallucination detection is increasingly important for evaluating and deploying large language models. However, existing methods are often compared across benchmarks that define and measure…
nlp
AV-FABLE: Audio-Visual Manipulation Forensics in Long-Form Videos
Localized AI manipulations in long-form videos often affect brief events within otherwise authentic content, making video-level classification insufficient for forensic analysis. Existing…
nlp
RynnUnify: Towards Unified Embodied Brain
We introduce RynnUnify, a 16B unified embodied model that combines strong embodied understanding with long-horizon visual planning through interleaved video--language reasoning. With capabilities…
nlp
On-Policy Self-Training: Data-Free Self-Improvement in Large Language Models
On-policy self-distillation enables post-training foundation models without relying on stronger external teachers. However, existing approaches rely on ground-truth question-answer pairs,…
deep-learning
A Broader Look into MLLM's Retrieval Heads
Locating relevant evidence in long inputs is a core capability of Multimodal Large Language Models. Prior studies attribute this capability to retrieval heads, a sparse set of attention heads that…
nlp
Sensorimotor Alignment: A Platonic Proxy for Embodied Policy Success
Robot foundation models are typically evaluated through costly closed-loop rollouts, motivating low-cost offline proxies for model capability. The Platonic Representation Hypothesis (PRH) suggests…
nlp
Reading, Writing, Sharing, and Interacting with the World through Video
Video foundation models have advanced rapidly in understanding and generating visual sequences, while video world models seek to capture the underlying dynamics of the world they depict. Despite…
computer-vision
Scaling in Games: Continued Pre-Training For Embodied Agents In Diverse Virtual Worlds
Scaling data, diversity and model capacity has improved embodied learning in physical environments, where diverse experiences remain grounded in shared physical laws. Whether these gains extend to…
computer-vision
Matrix-Game 4.0: Harnessing Video Models for Real-Time Playable Game Worlds
Moving from controllable videos to genuinely playable worlds requires persistent world state, executable game rules, and low-latency interaction. We outline a roadmap for the next generation of…
deep-learning
SpatialScout: Can VLM Agents Actively Explore and Map 3D Scenes?
Spatial intelligence requires agents to actively acquire visual evidence and integrate observations into a coherent representation of the three-dimensional world. Yet spatial question answering…
nlp