Tagged articles

large-scale dataset

4 articles · Page 1 of 1

Jul 6, 2026 · Artificial Intelligence

How a Million‑Scale 159‑Category Dataset and Foundation Model Set New Standards for Remote‑Sensing Object Detection

The paper introduces LEVIRDet‑159, the largest unified remote‑sensing detection dataset with 159 categories and 2.5 M annotations, and its foundation model LEVIRDetNet, which achieves state‑of‑the‑art performance on nine external benchmarks after a single training run, demonstrating strong cross‑scene generalization.

LEVIRDetcross-benchmark evaluationfoundation model

0 likes · 9 min read

How a Million‑Scale 159‑Category Dataset and Foundation Model Set New Standards for Remote‑Sensing Object Detection

Machine Heart

Apr 11, 2026 · Artificial Intelligence

How 100,000 Hours of Human Data Propelled Psi‑R2 to Lead MolmoSpaces

Lingchu AI demonstrates that scaling human‑operation data to nearly 100,000 hours, combined with a two‑model system and reinforcement learning, can replace costly robot‑teleoperation data and achieve top performance on the MolmoSpaces benchmark.

Psi-R2Psi-W0Reinforcement Learning

0 likes · 12 min read

How 100,000 Hours of Human Data Propelled Psi‑R2 to Lead MolmoSpaces

Amap Tech

Apr 14, 2025 · Artificial Intelligence

HumanRig: Learning Automatic Rigging for Humanoid Characters Using a Large‑Scale Dataset

HumanRig introduces a large‑scale dataset of 11,434 AI‑generated T‑pose humanoid meshes with unified skeletons, skinning weights, joint data and images, and leverages it in a novel automatic rigging pipeline—featuring a prior‑guided skeleton estimator, a U‑shaped point transformer, and a mesh‑skeleton mutual attention network—that significantly outperforms previous methods in skeleton accuracy and skinning quality.

3D animationAIautomatic rigging

0 likes · 12 min read

HumanRig: Learning Automatic Rigging for Humanoid Characters Using a Large‑Scale Dataset

NewBeeNLP

May 29, 2024 · Artificial Intelligence

How Ant’s Multimodal Team Boosted Video‑Text Retrieval by 24% and Cut Copyright Search Costs 85%

This article presents Ant Group's multimodal research on video retrieval, detailing a large Chinese video‑text pre‑training dataset, three techniques that raise video‑text semantic search performance by up to 24.5%, and an end‑to‑end video‑video copyright detection system that reduces storage by 85% and speeds up inference 18‑fold.

0 likes · 40 min read