idb
Datasets
All datasets matching “idb”meow-neuro-corpus-v02-artifacts
M.E.O.W. Neuro Corpus v0.2 — v2.3.1 Production Artifacts
This dataset repository contains the frozen v2.3.1 production artifacts for
the M.E.O.W. Neuro/Evil Neuro corpus. It contains derived structured data,
quality evidence, provenance, split authority, validators, and reproducibility
metadata. Raw video/audio, media slices, model weights, credentials, and source
transcripts are not redistributed.
Current release: v2.3.1
Pipeline:… See the full description on the dataset page: https://huggingface.co/datasets/ID-BLUEBERRY/meow-neuro-corpus-v02-artifacts.IDBench-Omni
IDBench-Omni
IDBench-Omni is a benchmark for controllable human-centric audio-video generation. It contains three tasks:
Task
Subsets
Samples
Inputs
Target
R2AV
single_person, multi_person
100
text prompt, reference identity image(s), reference voice audio(s)
generate synchronized video and audio
RA2V
default
50
text prompt, reference identity image, driving audio
animate the identity with the driving audio
RV2AV
swap_face, swap_human
50
text prompt, reference… See the full description on the dataset page: https://huggingface.co/datasets/XuGuo699/IDBench-Omni.stocks-IDBI-1D-candlesDouglas
Douglas
This dataset is created for Polar3D. Include 3D, 2D and Text asset
Dataset Details
Dataset Description
Dataset Sources [optional]
Repository: [More Information Needed]
Paper [optional]: [More Information Needed]
Demo [optional]: [More Information Needed]
Dataset Structure
GLB(Nonecessary)
NPZ--UUID--UUID.npz
2D--UUID--multiview.png /detailed_caption.txt /caption.txt /camera_info.txt
ALL-IDB-Patches
ALL-IDB Patches
MATLAB source code for creating image patches and labels used in the paper “ALL-IDB Patches: Whole slide imaging for Acute Lymphoblastic Leukemia detection using Deep Learning”, presented at ICASSP Workshops 2023.
The repository converts annotated ALL-IDB1 whole-slide microscope images into fixed-size overlapping patches, preserving the position of white blood cell centroids and generating patch-level labels for probable lymphoblasts… See the full description on the dataset page: https://huggingface.co/datasets/AngeloUNIMI/ALL-IDB-Patches.idb-invariant-compression-fidelity-v0.1
What this dataset tests
Whether compression keeps the invariant.
Not just the output.
A student can match answerswhile losing structure.
This benchmark detects that.
Why this exists
Compression can create proxy behavior.
The model learnswhat to saynot what must be preserved.
This set separates:
faithful retention
proxy matching
invariant loss
Data format
Each row contains:
original prompt and compressed prompt
teacher output and student output
an… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/idb-invariant-compression-fidelity-v0.1.