Upload folder using huggingface_hub

h5_files/3ET+/LICENSE.txt

@@ -0,0 +1,5 @@
+These samples are adapted from the 3ET+ dataset, which is released under the **CC BY 4.0 license**.
+
+[1] Q. Chen, Z. Wang, S. -C. Liu and C. Gao, "3ET: Efficient Event-based Eye Tracking using a Change-Based ConvLSTM Network," 2023 IEEE Biomedical Circuits and Systems Conference (BioCAS), Toronto, ON, Canada, 2023, pp. 1-5.
+[2] Z. Wang et al. "Event-based eye tracking. AIS 2024 challenge survey." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 5810-5825. 2024.
+[3] Q. Chen, et al. "Event-based eye tracking. Even-based Vision Workshop 2025." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025.

h5_files/Bully10K/LICENSE.txt

@@ -0,0 +1,4 @@
+These samples are adapted from the Bullying10K dataset, which is released under the **Creative Commons Attribution 4.0 license**.
+
+[1] Yiting Dong, Yang Li, Dongcheng Zhao, Guobin Shen, Yi Zeng. Bullying10K: A Neuromorphic Dataset towards Privacy-Preserving Bullying Recognition. figshare (2023).
+[2] Yiting Dong, Yang Li, Dongcheng Zhao, Guobin Shen, Yi Zeng. Bullying10K: A Neuromorphic Dataset towards Privacy-Preserving Bullying Recognition. arXiv preprint ArXiv. /abs/2306.11546 (2023).

h5_files/DSEC/LICENSE.txt

@@ -0,0 +1,4 @@
+These samples are adapted from the DSEC dataset, which is provided under the **Creative Commons Attribution-ShareAlike 4.0 International public license (CC BY-SA 4.0)**. Hence, the EvQA Team's contributions (which is the clipping and selection of these samples) is also under the same license.
+
+The original DSEC dataset:
+[1] Mathias Gehrig, Willem Aarents, Daniel Gehrig, and Davide Scaramuzza. DSEC: A Stereo Event Camera Dataset for Driving Scenarios. IEEE Robotics and Automation Letters, 2021.

h5_files/DailyDVS/LICENSE.txt

@@ -0,0 +1,3 @@
+These samples are adapted from the DailyDVS-200 dataset, which is released under the **MIT License**.
+
+[1] Qi Wang, Zhou Xu, Yuming Lin, Jingtao Ye, Hongsheng Li, Guangming Zhu, Syed Afaq Ali Shah, Mohammed Bennamoun, and Liang Zhang. DailyDVS-200: A Comprehensive Benchmark Dataset for Event-Based Action Recognition. arXiv preprint arXiv:2407.05106, 2024.

h5_files/DvsGesture/LICENSE.txt

@@ -0,0 +1,8 @@
+These samples are adapted from the DVS128 Gesture Dataset. The original LICENSE.txt is as follows:
+
+This work (DVS128 Gesture Dataset) is licensed under the Creative Commons
+Attribution 4.0 International License. To view a copy of this license, visit
+
+http://creativecommons.org/licenses/by/4.0/.
+
+For attribution, cite IBM Research (http://research.ibm.com/dvsgesture).

h5_files/EV-UAV/LICENSE.txt

@@ -0,0 +1,3 @@
+These samples are adapted from the EV-UAV dataset. Through email communication with the original authors, we learned that the original dataset is distributed under the **CC BY 4.0 license**.
+
+[1] Nuo Chen, Chao Xiao, Yimian Dai, Shiman He, Miao Li, and Wei An. Event-based Tiny Object Detection: A Benchmark Dataset and Baseline. In Proc. of the IEEE/CVF International Conference on Computer Vision (ICCV), 2025.

h5_files/EvAid/LICENSE.txt

@@ -0,0 +1,5 @@
+These samples are adapted from the EventAid dataset.
+
+[1] Peiqi Duan, Boyu Li, Yixin Yang, Hanyue Lou, Minggui Teng, Xinyu Zhou, Yi Ma, and Boxin Shi. EventAid: Benchmarking event-aided image/video enhancement algorithms with real-captured hybrid dataset. TPAMI 2025.
+
+Although no explicit license is provided with the original dataset, The EvQA Team has emailed the original authors and has been authorized to redistribute the dataset for the purpose of constructing a public question answering benchmark.

h5_files/EvBird/LICENSE.txt

@@ -0,0 +1,3 @@
+These samples are adapted from the EvBird sequences provided at https://github.com/HYLZ-2019/V2V.
+
+Although no explicit license is provided with the original dataset, The EvQA Team has emailed the original authors and has been authorized to redistribute the dataset for the purpose of constructing a public question answering benchmark.

h5_files/EvRealHands/LICENSE.txt

@@ -0,0 +1,5 @@
+These samples are adapted from the EvRealHands dataset.
+
+[1] EvHandPose: Event-based 3D Hand Pose Estimation with Sparse Supervision. Jianping, Jiang and Jiahe, Li and Baowen, Zhang and Xiaoming, Deng and Boxin, Shi. TPAMI 2024.
+
+Although no explicit license is provided with the original dataset, The EvQA Team has emailed the original authors and has been authorized to redistribute the dataset for the purpose of constructing a public question answering benchmark.

h5_files/EventFocalStack/LICENSE.txt

@@ -0,0 +1,5 @@
+These samples are adapted from the EventFocalStack dataset.
+
+[1] Hanyue Lou, Minggui Teng, Yixin Yang, and Boxin Shi. All-in-focus Imaging from Event Focal Stack. In Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
+
+Although no explicit license is provided with the original dataset, The EvQA Team has emailed the original authors and has been authorized to redistribute the dataset for the purpose of constructing a public question answering benchmark.

h5_files/EventPAR/LICENSE.txt

@@ -0,0 +1,27 @@
+These samples are adapted from the EventPAR dataset, which is provided under the **MIT License**.
+
+[1] Xiao Wang, Haiyang Wang, Shiao Wang, Qiang Chen, Jiandong Jin, Haoyu Song, Bo Jiang, and Chenglong Li. RGB-Event based Pedestrian Attribute Recognition: A Benchmark Dataset and An Asymmetric RWKV Fusion Framework. arXiv preprint, 2025.
+
+The original license is as follows:
+
+MIT License
+
+Copyright (c) 2023 Event-AHU
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

h5_files/EventPenguin/LICENSE.txt

@@ -0,0 +1,27 @@
+These samples are adapted from the EventPenguin dataset, which is provided under the **MIT License**.
+
+[1] Friedhelm Hamann, Suman Ghosh, Ignacio Juarez Martinez, Tom Hart, Alex Kacelnik, and Guillermo Gallego. Low-power Continuous Remote Behavioral Localization with Event Cameras. In Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
+
+The original license is as follows:
+
+MIT License
+
+Copyright (c) 2023 Friedhelm Hamann
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

h5_files/EventSTR/LICENSE.txt

@@ -0,0 +1,13 @@
+These samples are adapted from the EventSTR dataset, which is provided under the **MIT License**.
+
+[1] Xiao Wang, Jingtao Jiang, Dong Li, Futian Wang, Lin Zhu, Yaowei Wang, Yongyong Tian, and Jin Tang. EventSTR: A Benchmark Dataset and Baselines for Event Stream based Scene Text Recognition. arXiv preprint arXiv:2502.09020, 2025.
+
+The original license is as follows:
+
+Copyright © 2025 EventAHU
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

h5_files/EventVOT/LICENSE.txt

@@ -0,0 +1,5 @@
+These samples are adapted from the EventVOT dataset.
+
+[1] Xiao Wang, Shiao Wang, Chuanming Tang, Lin Zhu, Bo Jiang, Yonghong Tian, and Jin Tang. Event Stream-based Visual Object Tracking: A High-Resolution Benchmark Dataset and A Novel Baseline. In Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.
+
+Although no explicit license is provided with the original dataset, The EvQA Team has emailed the original authors and has been authorized to redistribute the dataset for the purpose of constructing a public question answering benchmark.

h5_files/FRED/LICENSE.txt

@@ -0,0 +1,3 @@
+These samples are adapted from the FRED dataset, which is licensed under the **Apache License 2.0**.
+
+[1] Gabriele Magrini, Niccolò Marini, Federico Becattini, Lorenzo Berlincioni, Niccolò Biondi, Pietro Pala, and Alberto Del Bimbo. FRED: The Florence RGB-Event Drone Dataset. arXiv preprint arXiv:2506.05163, 2025.

h5_files/HighREV/LICENSE.txt

@@ -0,0 +1,4 @@
+These samples are adapted from the HighREV dataset, which is licensed under the **Apache License 2.0**.
+
+[1] Lei Sun, Christos Sakaridis, Jingyun Liang, Peng Sun, Jiezhang Cao, Kai Zhang, Qi Jiang, Kaiwei Wang and Luc Van Gool. Event-Based Frame Interpolation with Ad-hoc Deblurring.  In Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR), 2023.
+[2] Lei Sun, Daniel Gehrig, Christos Sakaridis, Mathias Gehrig, Jingyun Liang, Peng Sun, Zhijie Xu, Kaiwei Wang, Luc Van Gool and Davide Scaramuzza. A unified framework for event-based frame interpolation with ad-hoc deblurring in the wild. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.

h5_files/IJRR/LICENSE.txt

@@ -0,0 +1,3 @@
+These samples are adapted from the IJRR dataset, which is released under the **Creative Commons license (CC BY-NC-SA 3.0)**.
+
+[1] Elias Mueggler, Henri Rebecq, Guillermo Gallego, Tobi Delbruck, and Davide Scaramuzza. The event camera dataset and simulator: Event-based data for pose estimation, visual odometry, and SLAM. International Journal of Robotics Research (IJRR), 2017.

h5_files/MTEvent/LICENSE.txt

@@ -0,0 +1,5 @@
+These samples are adapted from the MTEvent dataset.
+
+[1] Shrutarv Awasthi, Anas Gouda, Sven Franke, Jérôme Rutinowski, Frank Hoffmann, and Moritz Roidl. MTevent: A Multi-Task Event Camera Dataset for 6D Pose Estimation and Moving Object Detection. In Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2025.
+
+Although no explicit license is provided with the original dataset, The EvQA Team has emailed the original authors and has been authorized to redistribute the dataset for the purpose of constructing a public question answering benchmark.

h5_files/MouseSIS/LICENSE.txt

@@ -0,0 +1,27 @@
+These samples are adapted from the MouseSIS dataset, which is provided under the **MIT License**.
+
+[1] Friedhelm Hamann, Hanxiong Li, Paul Mieske, Lars Lewejohann, and Guillermo Gallego. MouseSIS: A Frames-and-Events Dataset for Space-Time Instance Segmentation of Mice. In Proc. of the European Conference on Computer Vision (ECCV) Workshops, 2024.
+
+The original license is as follows:
+
+MIT License
+
+Copyright (c) 2024 TU Berlin - Robotic Interactive Perception
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

h5_files/PEDRo/LICENSE.txt

@@ -0,0 +1,3 @@
+These samples are adapted from the PEDRo dataset, which is provided under the license Creative Commons Attribution 4.0 International (CC-BY-4.0).
+
+[1] Chiara Boretti, Philippe Bich, Fabio Pareschi, Luciano Prono, Riccardo Rovatti and Gianluca Setti. PEDRo: an Event-based Dataset for Person Detection in Robotics. In Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2023.

h5_files/eTraM/LICENSE.txt

@@ -0,0 +1,3 @@
+These samples are adapted from the eTraM dataset, which is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
+
+[1] Aayush Atul Verma, Bharatesh Chakravarthi, Arpitsinh Vaghela, Hua Wei, and Yezhou Yang. eTraM: Event-based Traffic Monitoring Dataset. In Proc. of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024.

questions/DailyDVS.json

@@ -1,6 +1,6 @@
 {
     "dataset_name": "DailyDVS",
-    "description": "Questions from the DailyDVS-200 dataset for event-based action recognition. DailyDVS-200 is a large-scale neuromorphic dataset for gesture and action recognition.",
+    "description": "Questions from the DailyDVS-200 dataset for event-based action recognition. DailyDVS-200 is a large-scale neuromorphic dataset for gesture and action recognition. References:\n[1] Qi Wang, Zhou Xu, Yuming Lin, Jingtao Ye, Hongsheng Li, Guangming Zhu, Syed Afaq Ali Shah, Mohammed Bennamoun, and Liang Zhang. DailyDVS-200: A Comprehensive Benchmark Dataset for Event-Based Action Recognition. arXiv preprint arXiv:2407.05106, 2024.",
     "questions": [
         {
             "question_id": "C0P31M1S4_20231127_09_58_53",