https://github.com/eth-sri/fairness-feedback-nlp
공식 코드Human-Guided Fair Classification for Natural Language Processing
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Style Transfer is a technique in computer vision and graphics that involves generating a new image by combining the content of one image with the style of another image. The goal of style transfer is to create an image that preserves the content of the original image while applying the visual style of another image.
<span style="color:grey; opacity: 0.6">( Image credit: A Neural Algorithm of Artistic Style )</span>
The "T" horizontal strip can mimic the back of a sofa with a delicate cushion or details of the uphols or appliances with the color button.
The "T" vertical strip can show a feet or arm of the sofa, shiny, yet firm.
Put "P" next to "T", your curve to delicately with the top "T." It is intertwined. The circular part of "P" can show a cushion or a curved chair and synchronize the subject of furniture.
Make sure "P" is visually relying on "T", which reflects the relationship of cohesion and balance.
"B" can be aligned as a pair of cushions or a modern chair, with mild curves with glossy and modern aesthetics.
"I" can be a symbol of a shiny furniture or a vertical light bar and completes the shapes without overburdess them.
Color palette 4:
Includes soft soil colors such as beige, top and gray shades, along with silent or silver gold tips to touch elegance.
Consider a slope effect to enhance modernity, to keep colors elegant and complex.
Use the overlap or intertwined edges that the letters meet for the symbol of unity.
The plan should allow viewers to distinguish each letter while feeling part of the same "structure".
Use delicate geometric patterns or textures that mimic fabrics or furniture materials such as wood seeds or woven fibers.
These patterns must remain minimalist and focus on highlighting the logo, while maintaining communication.
While it deals with the subject of furniture and design, this concept conveys modernity, creativity and professional. If you like, I can create a draft design for better visualization.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Human-Guided Fair Classification for Natural Language Processing
Style Transformer: Unpaired Text Style Transfer without Disentangled Latent Representation
Style Transformer: Unpaired Text Style Transfer without Disentangled Latent Representation
VAE based Text Style Transfer with Pivot Words Enhancement Learning
Bridging Unpaired Facial Photos And Sketches By Line-drawings
RLMiniStyler: Light-weight RL Style Agent for Arbitrary Sequential Neural Style Generation
FreeStyle: Free Lunch for Text-guided Style Transfer using Diffusion Models
WAIT: Feature Warping for Animation to Illustration video Translation using GANs
Domain Adaptive Sim-to-Real Segmentation of Oropharyngeal Organs
Investigating Societal Biases in a Poetry Composition System
Diversify Question Generation with Retrieval-Augmented Style Transfer
Ground-A-Video: Zero-shot Grounded Video Editing using Text-to-image Diffusion Models
Don't Take It Literally: An Edit-Invariant Sequence Loss for Text Generation
Regularization by Neural Style Transfer for MRI Field-Transfer Reconstruction with Limited Data
DeepDC: Deep Distance Correlation as a Perceptual Image Quality Evaluator
CreativeSynth: Cross-Art-Attention for Artistic Image Synthesis with Multimodal Diffusion
DiffStyler: Controllable Dual Diffusion for Text-Driven Image Stylization
Style-A-Video: Agile Diffusion for Arbitrary Text-based Video Style Transfer
TSSAT: Two-Stage Statistics-Aware Transformation for Artistic Style Transfer
Quality Evaluation of Arbitrary Style Transfer: Subjective Study and Objective Metric
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.