# Ethics and Creativity in Computer Vision

arXiv: https://arxiv.org/abs/2112.03111 · HTML: https://mlsanity.com/paper/2112.03111/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 9 references that are in the map.
- First posted on arXiv 6 Dec 2021.

## Builds on (most cited first, 4 of 4)

- [DeepFashion2: A Versatile Benchmark for Detection, Pose Estimation, Segmentation and Re-Identification of Clothing Images](https://mlsanity.com/paper/1901.07973/) (2019)
- [Fashion-Gen: The Generative Fashion Dataset and Challenge](https://mlsanity.com/paper/1806.08317/) (2018)
- [Biases in Generative Art -- A Causal Look from the Lens of Art History](https://mlsanity.com/paper/2010.13266/) (2020)
- [Predicting the Politics of an Image Using Webly Supervised Data](https://mlsanity.com/paper/1911.00147/) (2019)

## Built on by (most cited first, 15 of 15)

- [GAUDI: A Neural Architect for Immersive 3D Scene Generation](https://mlsanity.com/paper/2207.13751/) (2022)
- [CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling](https://mlsanity.com/paper/2310.17347/) (2023)
- [Eliminating Oversaturation and Artifacts of High Guidance Scales in Diffusion Models](https://mlsanity.com/paper/2410.02416/) (2024)
- [No Training, No Problem: Rethinking Classifier-Free Guidance for Diffusion Models](https://mlsanity.com/paper/2407.02687/) (2024)
- [Diffusion Probabilistic Fields](https://mlsanity.com/paper/2303.00165/) (2023)
- [LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models](https://mlsanity.com/paper/2405.14477/) (2024)
- [The Ethical Implications of Generative Audio Models: A Systematic Literature Review](https://mlsanity.com/paper/2307.05527/) (2023)
- [Rectified-CFG++ for Flow Based Models](https://mlsanity.com/paper/2510.07631/) (2025)
- [Guidance in the Frequency Domain Enables High-Fidelity Sampling at Low CFG Scales](https://mlsanity.com/paper/2506.19713/) (2025)
- [Manifold Diffusion Fields](https://mlsanity.com/paper/2305.15586/) (2023)
- [M-VADER: A Model for Diffusion with Multimodal Context](https://mlsanity.com/paper/2212.02936/) (2022)
- [Efficient Distillation of Classifier-Free Guidance using Adapters](https://mlsanity.com/paper/2503.07274/) (2025)
- [Perceptions and Realities of Text-to-Image Generation](https://mlsanity.com/paper/2306.08363/) (2023)
- [Generative Models are Self-Watermarked: Declaring Model Authentication through Re-Generation](https://mlsanity.com/paper/2402.16889/) (2024)
- [T1: Scaling Diffusion Probabilistic Fields to High-Resolution on Unified Visual Modalities](https://mlsanity.com/paper/2305.14674/) (2023)

## Abstract (arXiv)

This paper offers a retrospective of what we learnt from organizing the workshop *Ethical Considerations in Creative applications of Computer Vision* at CVPR 2021 conference and, prior to that, a series of workshops on *Computer Vision for Fashion, Art and Design* at ECCV 2018, ICCV 2019, and CVPR 2020. We hope this reflection will bring artists and machine learning researchers into conversation around the ethical and social dimensions of creative applications of computer vision.