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Part 1: Document Description
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Citation |
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Title: |
Replication Data for: Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision |
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Identification Number: |
doi:10.21979/N9/M41ERD |
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Distributor: |
DR-NTU (Data) |
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Date of Distribution: |
2024-06-20 |
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Version: |
1 |
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Bibliographic Citation: |
Wu, Haoning; Zhang, Zicheng; Zhang, Erli; Chen, Chaofeng; Liao, Liang; Wang, Annan; Li, Chunyi; Sun, Wenxiu; Yan, Qiong; Zhai, Guangtao; Lin, Weisi, 2024, "Replication Data for: Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision", https://doi.org/10.21979/N9/M41ERD, DR-NTU (Data), V1 |
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Citation |
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Title: |
Replication Data for: Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision |
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Identification Number: |
doi:10.21979/N9/M41ERD |
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Authoring Entity: |
Wu, Haoning (Nanyang Technological University) |
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Zhang, Zicheng (Shanghai Jiaotong University) |
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Zhang, Erli (Nanyang Technological University) |
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Chen, Chaofeng (Nanyang Technological University) |
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Liao, Liang (Nanyang Technological University) |
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Wang, Annan (Nanyang Technological University) |
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Li, Chunyi (Shanghai Jiaotong University) |
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Sun, Wenxiu (Sensetime Research) |
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Yan, Qiong (Sensetime Research) |
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Zhai, Guangtao (Shanghai Jiaotong University) |
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Lin, Weisi (Nanyang Technological University) |
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Software used in Production: |
NIL |
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Grant Number: |
the RIE2020 Industry Alignment Fund |
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Distributor: |
DR-NTU (Data) |
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Access Authority: |
Wu, Haoning |
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Depositor: |
Chen, Chaofeng |
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Date of Deposit: |
2024-06-20 |
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Holdings Information: |
https://doi.org/10.21979/N9/M41ERD |
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Study Scope |
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Keywords: |
Computer and Information Science, Computer and Information Science, Image Quality Assessment, Large Multi-modality Models |
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Abstract: |
We present Q-Bench, a holistic benchmark crafted to systematically evaluate potential abilities of MLLMs on three realms: low-level visual perception, low-level visual description, and overall visual quality assessment. |
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Kind of Data: |
Survey data |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
S-Lab License 1.0<br> Copyright 2022 S-Lab<br> <br> Redistribution and use for non-commercial purpose in source and binary forms, with or without modification, are permitted provided that the following conditions are met:<br> 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.<br> 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.<br> 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.<br> <br> THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. <br><br> In the event that redistribution and/or use for commercial purpose in source or binary forms, with or without modification is required, please contact the contributor(s) of the work. |
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Other Study Description Materials |
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Related Studies |
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The github project page is: <a href="https://github.com/Q-Future/Q-Bench">https://github.com/Q-Future/Q-Bench</a><br> The public download link is: <a href="https://huggingface.co/datasets/teowu/LLVisionQA-QBench">https://huggingface.co/datasets/teowu/LLVisionQA-QBench</a> |
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Related Publications |
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Citation |
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Identification Number: |
2309.14181v3 |
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Bibliographic Citation: |
Wu, H., Zhang, Z., Zhang, E., Chen, C., Liao, L., Wang, A., Li, C., Sun, W., Yan, Q., Zhai, G. & Lin, W. (2024). Q-bench: a benchmark for general-purpose foundation models on low-level vision. 12th International Conference on Learning Representations (ICLR 2024). |
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Citation |
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Identification Number: |
10356/178462 |
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Bibliographic Citation: |
Wu, H., Zhang, Z., Zhang, E., Chen, C., Liao, L., Wang, A., Li, C., Sun, W., Yan, Q., Zhai, G. & Lin, W. (2024). Q-bench: a benchmark for general-purpose foundation models on low-level vision. 12th International Conference on Learning Representations (ICLR 2024). |