arXiv (All)
open access
Generating the Wild: Individual-Consistent Image-to-Video Generation for Wildlife
Individual-level wildlife identification often suffers from data scarcity, as varying observations of the same animal under diverse poses, viewpoints, and motions are rarely available. Image-to-video (I2V) generation offers a promising way to mitigate this limitation by synthesizing additional obser
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
- EntityBench: Towards Entity-Consistent Long-Range Multi-Shot Video Generation#187340
- Biodiversity at OBSEA seabed observatory 2021#983720
- ScenePlacer: Reformulating Scene-Level Object Pose Estimation as Visibility Field Learning#1326984
- VIEScore2: Unified Image Evaluation with Spatially Grounded Explanations#1155929
- Video2SwimFish: An Automated Pipeline for Reconstructing Controllable Fish Models and Biological Locomotion from Real Fish Videos#1143933
Record · ID 1201600
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