3dgen user study

config.yaml

@@ -1,8 +1,8 @@
 method_filter:
-  - video_model1
-  - video_model2
+  - 3dgen_1
+  - 3dgen_2
 period_upload: 300  #  Period (sec) to upload response files in seconds, 300sec=5min
 period_squash: 43200  # Period (sec) to squash commits in seconds, 43200sec=12h
 ask_user_id: True
 id_platform: Prolific
-task: Video_Internal
+task: 3DGen_Internal

detail.md

@@ -1,17 +1,13 @@
-# A Video Quality User Study for Video Diffusion Models
-Are you interested in the latest developments in video diffusion models? We invite you to participate in our user study, where you can watch a few images samples and provide your ratings. By participating, you will have the chance to experience the latest video diffusion models firsthand. The study should take as little as 1 minute to complete.
+# A 3D Multi-View Synthesis Quality User Study for 3D Multi-View Synthesis Models
+Are you interested in the latest developments in 3D multi-view synthesis models? We invite you to participate in our user study, where you can watch a few video samples and provide your ratings. By participating, you will have the chance to experience the latest 3D multi-view synthesis models firsthand. The study should take as little as 1 minute to complete.
 
-### What Are We Evaluating?
-This study aims to assess the quality of different frames generated by one diffusion-based generative models. We are focusing on key aspects such as spatial and temporal consistency, as well as multi-view coherence. While these models produce impressive results, they can also generate unexpected artifacts, such as strange morphing effects, abrupt changes in subjects, or unusual occlusions and geometries. We have created 50 videos for this study. 
+## What Are We Evaluating?
+This study aims to assess the quality of generated videos from two different 3D multi-view synthesis models. We are focusing on key aspects such as spatial and temporal consistency, as well as multi-view coherence. While these models produce impressive results, they can also generate unexpected artifacts, such as strange morphing effects, abrupt changes in subjects, or unusual occlusions and geometries. We have created 50 renderings for this study; each rendering is generated using identical poses across the two models, and we may expand the study to include more renderings and additional models in the future. 
 
-| ![GIF 1](example/good.gif) | ![GIF 2](example/bad.gif) |
-|:---------------------------------------------------------------------------:|:---------------------------------------------------------------------------:|
-| 🙂 Pretty Good                                                           |  🤔 Subject changed and weird books.                                                              |
+## Your Contribution Matters
+The results of this study, along with the 3D multi-view synthesis models used, will be made publicly available as part of a dataset. This dataset will contribute to a research report aimed at advancing the understanding of 3D multi-view synthesis models. Your feedback is crucial in helping us identify and understand these phenomena.
 
-### Your Contribution Matters
-The results of this study, along with the videos and prompts used, will be made publicly available as part of a dataset. This dataset will contribute to a research report aimed at advancing the understanding of video diffusion models. Your feedback is crucial in helping us identify and understand these phenomena. 
+## How to Participate
+You can join the study using any device—whether it is a phone, tablet, laptop, or desktop computer. For the best experience, we recommend using a larger screen to observe potential artifacts more clearly. Please note that some mobile devices may have energy-saving settings that prevent videos from autoplaying. If this happens, simply click on the video boxes to play them manually.
 
-### How to Participate
-You can join the study using any device, whether it is a phone, tablet, laptop, or desktop computer. 
-
-Your participation is invaluable to us. Thank you for contributing to the advancement of video diffusion technology. 
+Your participation is invaluable to us. Thank you for contributing to the advancement of 3D multi-view synthesis models.

start.md

@@ -1,4 +1,4 @@
-# 🧐 Video Quality Study (Image Level)
+# 🧐 Generation Quality Study (Image Level)
 🙏 Thank you for participating our study! This study should take ~1 minute.
 
-💼 Task: You'll watch 2 pairs of images. For each pair, select the image that <mark> has better quality, and with less noise. </mark>
+💼 Task: You'll see multi-view images rendering from 2 methods. Select the method that <mark> has better quality, multi-view consistency, and with less noise. </mark>