https://github.com/bytedance/uno
공식 코드Less-to-More Generalization: Unlocking More Controllability by In-Context Generation
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The development of the brain's blood supply in an embryo involves a complex process with several stages. Initially, there is a network of connections between the carotid and basilar artery systems that usually disappear during development. However, in some cases, these connections remain, leading to variations in the adult cerebral circulation. Around the 24th day of embryonic life (at the 3 mm embryonic stage), the internal carotid arteries (ICA) emerge. They are formed from a combination of the 3rd branchial arch arteries and the distal segments of the paired dorsal aortae. The ICA initially provides all the blood needed by the developing brain. As the brain grows, particularly the occipital region, brainstem, and cerebellum, the blood supply from the ICA becomes insufficient, prompting the development of the posterior circulation. At this stage (4-5 mm embryonic stage), the posterior circulation, specifically the hindbrain, is supplied by two longitudinal neural arteries. These arteries receive blood from several temporary connections (anastomoses) with the ICA, including: Trigeminal artery (TA), Otic artery (OA), Hypoglossal artery (HA), Proatlantal artery (ProA). These carotid-vertebrobasilar anastomoses act as temporary bridges, providing blood flow to the developing posterior circulation until the vertebral arteries (VA) and the basilar artery (BA) are fully formed.6
The BA forms between the 5-8 mm stage by the fusion of the longitudinal neural arteries. As the posterior communicating artery develops and connects with the distal BA, the TA, OA, and HA typically regress. Unlike the TA, OA, and HA, the ProA persists until the VA are fully developed. A segment of the ProA becomes incorporated into the V3 segment of the VA and the distal portions of the occipital artery. The VA develop between the 7-12 mm stage from transverse connections between cervical intersegmental arteries, starting with the ProA and progressing downwards to the 6th intersegmental artery. This 6th intersegmental artery eventually forms the origin of the adult VA from the subclavian artery. 7-8
Persistence of the HA into adulthood, the focus of this discussion, is a rare occurrence. It is the second most common persistent carotid-vertebrobasilar anastomosis, following the persistent trigeminal artery. The failure of the HA to regress during embryological development leads to PPHA. This condition can impact the normal blood flow dynamics in the brain and, in certain cases, can be associated with cerebrovascular issues like aneurysms or ischemic events.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Less-to-More Generalization: Unlocking More Controllability by In-Context Generation
XVerse: Consistent Multi-Subject Control of Identity and Semantic Attributes via DiT Modulation
CoMat: Aligning Text-to-Image Diffusion Model with Image-to-Text Concept Matching
T2I-R1: Reinforcing Image Generation with Collaborative Semantic-level and Token-level CoT
What the DAAM: Interpreting Stable Diffusion Using Cross Attention
FlexDiT: Dynamic Token Density Control for Diffusion Transformer
Character-Adapter: Prompt-Guided Region Control for High-Fidelity Character Customization
Likelihood-Based Text-to-Image Evaluation with Patch-Level Perceptual and Semantic Credit Assignment
ImagenHub: Standardizing the evaluation of conditional image generation models
Generation Of Colors using Bidirectional Long Short Term Memory Networks
Generation Of Colors using Bidirectional Long Short Term Memory Networks
MemBench: Memorized Image Trigger Prompt Dataset for Diffusion Models
Vector Quantized Diffusion Model for Text-to-Image Synthesis
Relations, Negations, and Numbers: Looking for Logic in Generative Text-to-Image Models
Multimodal Foundation Models: From Specialists to General-Purpose Assistants
ConceptBed: Evaluating Concept Learning Abilities of Text-to-Image Diffusion Models
Beyond Fine-Tuning: A Systematic Study of Sampling Techniques in Personalized Image Generation
Curriculum Direct Preference Optimization for Diffusion and Consistency Models
Reverse Stable Diffusion: What prompt was used to generate this image?
Improving the Stability and Efficiency of Diffusion Models for Content Consistent Super-Resolution
ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generation
MasterWeaver: Taming Editability and Face Identity for Personalized Text-to-Image Generation
InstaStyle: Inversion Noise of a Stylized Image is Secretly a Style Adviser
Direct Inversion: Boosting Diffusion-based Editing with 3 Lines of Code
PathLDM: Text conditioned Latent Diffusion Model for Histopathology
Is synthetic data from generative models ready for image recognition?
Magic 1-For-1: Generating One Minute Video Clips within One Minute
Swap Attention in Spatiotemporal Diffusions for Text-to-Video Generation
Lasagna: Layered Score Distillation for Disentangled Object Relighting
Learning to Sample Effective and Diverse Prompts for Text-to-Image Generation
Face-MakeUp: Multimodal Facial Prompts for Text-to-Image Generation
DesignEdit: Multi-Layered Latent Decomposition and Fusion for Unified & Accurate Image Editing
RadAlign: Advancing Radiology Report Generation with Vision-Language Concept Alignment
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.