wide
Datasets
All datasets matching “wide”WideSearch
WideSearch: Benchmarking Agentic Broad Info-Seeking
Dataset Summary
WideSearch is a benchmark designed to evaluate the capabilities of Large Language Model (LLM) driven agents in broad information-seeking tasks. Unlike existing benchmarks that focus on finding a single, hard-to-find fact, WideSearch assesses an agent's ability to handle tasks that require gathering a large amount of scattered, yet easy-to-find, information.
The challenge in these tasks lies not in… See the full description on the dataset page: https://huggingface.co/datasets/ByteDance-Seed/WideSearch.WideDepth
WideDepth: Millimeter-Accurate Benchmark for Fisheye Depth Estimation
WideDepth is the first indoor dataset for fisheye depth estimation, featuring 101 scenes containing 5K high-resolution stereo pairs labeled with millimeter-level ground truth depth and disparity.
Paper: WideDepth: Millimeter-Accurate Benchmark for Fisheye Depth Estimation
Project Page: https://ilyaind.github.io/WideDepth
The dataset includes paired pinhole and fisheye samples across varying fields of view… See the full description on the dataset page: https://huggingface.co/datasets/IlyaInd/WideDepth.wider_faceWIDER FACE dataset is a face detection benchmark dataset, of which images are
selected from the publicly available WIDER dataset. We choose 32,203 images and
label 393,703 faces with a high degree of variability in scale, pose and
occlusion as depicted in the sample images. WIDER FACE dataset is organized
based on 61 event classes. For each event class, we randomly select 40%/10%/50%
data as training, validation and testing sets. We adopt the same evaluation
metric employed in the PASCAL VOC dataset. Similar to MALF and Caltech datasets,
we do not release bounding box ground truth for the test images. Users are
required to submit final prediction files, which we shall proceed to evaluate.chocopan-t3-reverse-oracle-hdf5-wide-v1
chocopan-t3-reverse-oracle-hdf5-wide-v1
Raw HDF5 output of a scripted oracle for reverse manipulation tasks in simulation -- take an object out of a container or off a plate and put it back on the table -- for the batch generated with widened object initial placements: 7,200 attempts over 45 tasks, failures included.
This is the raw, unfiltered output of the generator, in LIBERO's create_dataset.py HDF5
layout. It is published because it is bulky to regenerate, not because it is… See the full description on the dataset page: https://huggingface.co/datasets/chocopan/chocopan-t3-reverse-oracle-hdf5-wide-v1.Wider_FaceSegLitewidedepth
Dataset Card for WideDepth in FiftyOne
FiftyOne dataset for WideDepth — an indoor fisheye depth-estimation benchmark (ICRA 2026) with millimeter-accurate ground-truth depth and disparity rendered from high-resolution LiDAR scans.
We use one fixed camera configuration from the full WideDepth benchmark — 195° FOV, 300 mm focal length, CENTER stereo position — across all 101 indoor scenes.
The full Hub release has many combinations (4 FOVs × 5 focal lengths × 3 positions, plus… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/widedepth.