{"work":{"id":"9d8a82a0-b08a-44fe-9165-95aded3e32be","openalex_id":null,"doi":null,"arxiv_id":"2404.09990","raw_key":null,"title":"HQ-Edit: A High-Quality Dataset for Instruction-based Image Editing","authors":null,"authors_text":"Hui, M","year":2024,"venue":"cs.CV","abstract":"This study introduces HQ-Edit, a high-quality instruction-based image editing dataset with around 200,000 edits. Unlike prior approaches relying on attribute guidance or human feedback on building datasets, we devise a scalable data collection pipeline leveraging advanced foundation models, namely GPT-4V and DALL-E 3. To ensure its high quality, diverse examples are first collected online, expanded, and then used to create high-quality diptychs featuring input and output images with detailed text prompts, followed by precise alignment ensured through post-processing. In addition, we propose two evaluation metrics, Alignment and Coherence, to quantitatively assess the quality of image edit pairs using GPT-4V. HQ-Edits high-resolution images, rich in detail and accompanied by comprehensive editing prompts, substantially enhance the capabilities of existing image editing models. For example, an HQ-Edit finetuned InstructPix2Pix can attain state-of-the-art image editing performance, even surpassing those models fine-tuned with human-annotated data. The project page is https://thefllood.github.io/HQEdit_web.","external_url":"https://arxiv.org/abs/2404.09990","cited_by_count":null,"metadata_source":"pith","metadata_fetched_at":"2026-07-09T21:16:34.372456+00:00","pith_arxiv_id":"2404.09990","created_at":"2026-05-09T06:55:44.330222+00:00","updated_at":"2026-07-09T21:16:34.372456+00:00","title_quality_ok":true,"display_title":"Hq-edit: A high-quality dataset for instruction-based image editing","render_title":"Hq-edit: A high-quality dataset for instruction-based image editing"},"hub":{"state":{"work_id":"9d8a82a0-b08a-44fe-9165-95aded3e32be","tier":"hub","tier_reason":"10+ Pith inbound or 1,000+ external citations","pith_inbound_count":27,"external_cited_by_count":null,"distinct_field_count":1,"first_pith_cited_at":"2025-04-17T17:24:23+00:00","last_pith_cited_at":"2026-07-08T06:26:28+00:00","author_build_status":"not_needed","summary_status":"needed","contexts_status":"needed","graph_status":"needed","ask_index_status":"not_needed","reader_status":"not_needed","recognition_status":"not_needed","updated_at":"2026-08-22T19:49:35.602502+00:00","tier_text":"hub"},"tier":"hub","role_counts":[{"context_role":"background","n":3},{"context_role":"dataset","n":3}],"polarity_counts":[{"context_polarity":"background","n":3},{"context_polarity":"use_dataset","n":2},{"context_polarity":"baseline","n":1}],"runs":{},"summary":{},"graph":{},"authors":[]}}