arXiv (All)
open access
ScribbleEdit: A Benchmark for Scribble-Only Image Editing
Scribble-based interaction provides a lightweight and intuitive way for users to specify image editing intents in interactive editing tools. However, current image editing models based on VLMs or LLMs struggle to understand and execute edits based solely on scribble inputs. To systematically study t
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Edit-Compass & EditReward-Compass: A Unified Benchmark for Image Editing and Reward Modeling#1202061
- MixDetect: Word-Level Localization and Quantification of AI Editing#1116956
- Drag as Evidence: Motion-Grounded Latent Recomposition for Drag-Based Editing#1131956
- V-JEPA Policy: Building Effective World-Action Models on Predictive Visual Latents#1141294
- SpatialGuard: Harness-Guided Verifiable Spatial Reasoning for Text-to-Image Generation#821606
Record · ID 1233421
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive