{"url":"/dataset/housecat6d","name":"HouseCat6D","full_name":"A Large-Scale Multi-Modal Category Level 6D Object Perception Dataset with Household Objects in Realistic Scenarios","description_markdown":"Estimating 6D object poses is a major challenge in 3D computer vision. Building on successful instance-level approaches, research is shifting towards category-level pose estimation for practical applications. Current categorylevel datasets, however, fall short in annotation quality and pose variety. Addressing this, we introduce HouseCat6D, a new category-level 6D pose dataset. It features 1) multimodality with Polarimetric RGB and Depth (RGBD+P), 2) encompasses 194 diverse objects across 10 household categories, including two photometrically challenging ones, and 3) provides high-quality pose annotations with an error range of only 1.35 mm to 1.74 mm. The dataset also includes 4) 41 large-scale scenes with comprehensive viewpoint and occlusion coverage, 5) a checkerboard-free environment, and 6) dense 6D parallel-jaw robotic grasp annotations. Additionally, we present benchmark results for leading category-level pose estimation networks.","description_withheld":null,"homepage":"https://sites.google.com/view/housecat6d/about","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":{"name":"CC BY 4.0","url":null},"modalities":[{"name":"RGB-D","url":"/datasets/modality/rgb-d"}],"tasks":[{"name":"6D Pose Estimation","url":"/task/6d-pose-estimation-1","datasets_with_task":"/datasets/task/6d-pose-estimation-1"},{"name":"Robotic Grasping","url":"/task/robotic-grasping","datasets_with_task":"/datasets/task/robotic-grasping"}],"languages":[],"variants":["HouseCat6D"],"data_loaders":[],"num_papers_in_archive":0,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}