Datasets:

Louischong
/

ICCV_workshop_test

@@ -20,7 +20,7 @@ conditions, overcoming the limitations of static datasets.
 This challenge focus on the **second question**. If you have interest on the first one, please refer to [another competition](https://huggingface.co/spaces/XDimLab/ICCV2025-RealADSim-NVS).
 ## Task Description
-![teaser](https://huggingface.co/datasets/XDimLab/competition_public_dataset/resolve/main/competition2.png)
 The challenge focuses on evaluating novel autonomous driving algorithms based on [HUGSIM](https://github.com/hyzhou404/HUGSIM). Our closed-loop simulator will provide challenging variety of photo-realistic urban scenarios, including oncoming traffic and cut-in driving behaviors.
 Unlike typical challenges that require submissions as static files, this workshop requires models and code as submissions due to the nature of closed-loop simulation. Specifically, the interaction between autonomous driving algorithms and the simulator is unpredictable, and results will only be available once the simulation concludes.

 This challenge focus on the **second question**. If you have interest on the first one, please refer to [another competition](https://huggingface.co/spaces/XDimLab/ICCV2025-RealADSim-NVS).
 ## Task Description
+![teaser](https://huggingface.co/datasets/XDimLab/competition_public_dataset/resolve/main/competition_2.png)
 The challenge focuses on evaluating novel autonomous driving algorithms based on [HUGSIM](https://github.com/hyzhou404/HUGSIM). Our closed-loop simulator will provide challenging variety of photo-realistic urban scenarios, including oncoming traffic and cut-in driving behaviors.
 Unlike typical challenges that require submissions as static files, this workshop requires models and code as submissions due to the nature of closed-loop simulation. Specifically, the interaction between autonomous driving algorithms and the simulator is unpredictable, and results will only be available once the simulation concludes.