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Found 10 papers, 4 papers with code
BeautifulPrompt: Towards Automatic Prompt Engineering for Text-to-Image Synthesis
Then, to ensure that our generated prompts can generate more beautiful images, we further propose a Reinforcement Learning with Visual AI Feedback technique to fine-tune our model to maximize the reward values of the generated prompts, where the reward values are calculated based on the PickScore and the Aesthetic Scores.
Hierarchical Side-Tuning for Vision Transformers
Fine-tuning pre-trained Vision Transformers (ViT) has consistently demonstrated promising performance in the realm of visual recognition.
EasyPhoto: Your Smart AI Photo Generator
By training a digital doppelganger of a specific user ID using 5 to 20 relevant images, the finetuned model (according to the trained LoRA model) allows for the generation of AI photos using arbitrary templates.
DualToken-ViT: Position-aware Efficient Vision Transformer with Dual Token Fusion
Position-aware global tokens also contain the position information of the image, which makes our model better for vision tasks.
FaceChain: A Playground for Human-centric Artificial Intelligence Generated Content
In this paper, we present FaceChain, a personalized portrait generation framework that combines a series of customized image-generation model and a rich set of face-related perceptual understanding models (\eg, face detection, deep face embedding extraction, and facial attribute recognition), to tackle aforementioned challenges and to generate truthful personalized portraits, with only a handful of portrait images as input.
DiffSynth: Latent In-Iteration Deflickering for Realistic Video Synthesis
In recent years, diffusion models have emerged as the most powerful approach in image synthesis.
Scale-Aware Modulation Meet Transformer
Specifically, SMT with 11. 5M / 2. 4GFLOPs and 32M / 7. 7GFLOPs can achieve 82. 2% and 84. 3% top-1 accuracy on ImageNet-1K, respectively.
SC-ML: Self-supervised Counterfactual Metric Learning for Debiased Visual Question Answering
Unfortunately, language bias is a common problem in VQA, which refers to the model generating answers only by associating with the questions while ignoring the visual content, resulting in biased results.
YOLOX-PAI: An Improved YOLOX, Stronger and Faster than YOLOv6
We develop an all-in-one computer vision toolbox named EasyCV to facilitate the use of various SOTA computer vision methods.
Elastic-Link for Binarized Neural Network
For example, we raise the top-1 accuracy of binarized ResNet26 from 57. 9% to 64. 0%.
