Text-to-Image 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.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/naver-ai/mid.metric
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https://github.com/nctu-eva-lab/antifakeprompt
공식 코드AntifakePrompt: Prompt-Tuned Vision-Language Models are Fake Image Detectors
https://github.com/nihukat/freegraftor
공식 코드FreeGraftor: Training-Free Cross-Image Feature Grafting for Subject-Driven Text-to-Image Generation
https://github.com/nju-pcalab/rag-diffusion
공식 코드Region-Aware Text-to-Image Generation via Hard Binding and Soft Refinement
https://github.com/nms05/improving-concept-alignment-in-vision-language-concept-bottleneck-models
공식 코드Improving Concept Alignment in Vision-Language Concept Bottleneck Models
https://github.com/noagarcia/phase
공식 코드Uncurated Image-Text Datasets: Shedding Light on Demographic Bias
https://github.com/noamelata/nesteddiffusion
공식 코드https://github.com/nzilberstein/Repulsive-score-distillation-RSD-
공식 코드Repulsive Latent Score Distillation for Solving Inverse Problems
https://github.com/oanaignat/mosaig
공식 코드Multi-Agent Multimodal Models for Multicultural Text to Image Generation
https://github.com/ofa-sys/ofa
공식 코드https://github.com/omerbt/MultiDiffusion
공식 코드MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation
https://github.com/omnai-lab/implicit-inversion
공식 코드https://github.com/omriav/blended-diffusion
공식 코드https://github.com/omriav/blended-latent-diffusion
공식 코드https://github.com/open-mmlab/anycontrol
공식 코드AnyControl: Create Your Artwork with Versatile Control on Text-to-Image Generation
https://github.com/openai/DALL-E
공식 코드https://github.com/openai/glide-text2im
공식 코드GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
https://github.com/openbmb/viscpm
공식 코드Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages
https://github.com/opengvlab/instruct2act
공식 코드Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model
https://github.com/oppo-mente-lab/facescore
공식 코드FaceScore: Benchmarking and Enhancing Face Quality in Human Generation
https://github.com/oppo-mente-lab/x2i
공식 코드https://github.com/optml-group/advunlearn
공식 코드Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models
https://github.com/optml-group/unlearncanvas
공식 코드UnlearnCanvas: Stylized Image Dataset for Enhanced Machine Unlearning Evaluation in Diffusion Models
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공식 코드MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing
https://github.com/paint4poem/paint4poem
공식 코드Paint4Poem: A Dataset for Artistic Visualization of Classical Chinese Poems
https://github.com/panqihe-zjut/SOEBench
공식 코드Towards Small Object Editing: A Benchmark Dataset and A Training-Free Approach
https://github.com/patchwork53/asymmetricattack
공식 코드Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks
https://github.com/pengbo807/ConditionVideo
공식 코드ConditionVideo: Training-Free Condition-Guided Text-to-Video Generation
https://github.com/picsart-ai-research/zero-painter
공식 코드Zero-Painter: Training-Free Layout Control for Text-to-Image Synthesis
https://github.com/pioneerAlpha/BanglaText2ImageGeneration
공식 코드https://github.com/pix2pixzero/pix2pix-zero
공식 코드https://github.com/pku-dair/hetu
공식 코드Accelerating Text-to-Image Editing via Cache-Enabled Sparse Diffusion Inference
https://github.com/pku-yuangroup/imgedit
공식 코드https://github.com/pku-yuangroup/wise
공식 코드WISE: A World Knowledge-Informed Semantic Evaluation for Text-to-Image Generation
https://github.com/pluslabnlp/vp-csv
공식 코드Character-Centric Story Visualization via Visual Planning and Token Alignment
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.