Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
[Journal club] Scalable Diffusion Models with T...
Search
Semantic Machine Intelligence Lab., Keio Univ.
PRO
July 22, 2024
Technology
0
130
[Journal club] Scalable Diffusion Models with Transformers
Semantic Machine Intelligence Lab., Keio Univ.
PRO
July 22, 2024
Tweet
Share
More Decks by Semantic Machine Intelligence Lab., Keio Univ.
See All by Semantic Machine Intelligence Lab., Keio Univ.
FlowAR: Scale-wise Autoregressive Image Generation Meets Flow Matching
keio_smilab
PRO
0
2
[Journal club] VLA-Adapter: An Effective Paradigm for Tiny-Scale Vision-Language-Action Model
keio_smilab
PRO
0
70
[Journal club] Improved Mean Flows: On the Challenges of Fastforward Generative Models
keio_smilab
PRO
0
140
[Journal club] MemER: Scaling Up Memory for Robot Control via Experience Retrieval
keio_smilab
PRO
0
87
[Journal club] Flow Matching for Generative Modeling
keio_smilab
PRO
1
340
Multimodal AI Driving Solutions to Societal Challenges
keio_smilab
PRO
2
200
[Journal club] Re-thinking Temporal Search for Long-Form Video Understanding
keio_smilab
PRO
0
47
[Journal club] Focusing on What Matters: Object-Agent-centric Tokenization for Vision Language Action Models
keio_smilab
PRO
0
20
[Journal club] EXPERT: An Explainable Image Captioning Evaluation Metric with Structured Explanations
keio_smilab
PRO
0
75
Other Decks in Technology
See All in Technology
What happened to RubyGems and what can we learn?
mikemcquaid
0
310
配列に見る bash と zsh の違い
kazzpapa3
3
160
外部キー制約の知っておいて欲しいこと - RDBMSを正しく使うために必要なこと / FOREIGN KEY Night
soudai
PRO
12
5.6k
予期せぬコストの急増を障害のように扱う――「コスト版ポストモーテム」の導入とその後の改善
muziyoshiz
1
2k
データの整合性を保ちたいだけなんだ
shoheimitani
8
3.2k
プロダクト成長を支える開発基盤とスケールに伴う課題
yuu26
4
1.4k
Ruby版 JSXのRuxが気になる
sansantech
PRO
0
160
usermode linux without MMU - fosdem2026 kernel devroom
thehajime
0
240
私たち準委任PdEは2つのプロダクトに挑戦する ~ソフトウェア、開発支援という”二重”のプロダクトエンジニアリングの実践~ / 20260212 Naoki Takahashi
shift_evolve
PRO
1
110
Tebiki Engineering Team Deck
tebiki
0
24k
ブロックテーマでサイトをリニューアルした話 / 2026-01-31 Kansai WordPress Meetup
torounit
0
480
顧客の言葉を、そのまま信じない勇気
yamatai1212
1
360
Featured
See All Featured
Sam Torres - BigQuery for SEOs
techseoconnect
PRO
0
190
The Spectacular Lies of Maps
axbom
PRO
1
530
Abbi's Birthday
coloredviolet
1
4.8k
How to build an LLM SEO readiness audit: a practical framework
nmsamuel
1
650
Git: the NoSQL Database
bkeepers
PRO
432
66k
Evolution of real-time – Irina Nazarova, EuRuKo, 2024
irinanazarova
9
1.2k
Gemini Prompt Engineering: Practical Techniques for Tangible AI Outcomes
mfonobong
2
280
From π to Pie charts
rasagy
0
130
Efficient Content Optimization with Google Search Console & Apps Script
katarinadahlin
PRO
1
330
From Legacy to Launchpad: Building Startup-Ready Communities
dugsong
0
140
The Impact of AI in SEO - AI Overviews June 2024 Edition
aleyda
5
740
Raft: Consensus for Rubyists
vanstee
141
7.3k
Transcript
4DBMBCMF%JGGVTJPO.PEFMTXJUI 5SBOTGPSNFST ܚጯٛक़େֶ ਿӜ໌ݚڀࣨ#ീౡେ 8JMMJBN1FFCMFT 4BJOJOH9JF 6$#FSLFMFZ /FX:PSL6OJWFSTJUZ *$$7 8JMMJBN1FFCMFT
4BJOJOH9JFl4DBMBCMF%JGGVTJPO.PEFMTXJUI5SBOTGPSNFSTzJO*$$7 QQ
എܠɿ֦ࢄϞσϧʹΑΔಈը૾ੜ FH 4PSB ͷൃల IUUQTXXXZPVUVCFDPNXBUDI W),Z%"1/@
ؔ࿈ݚڀɿ֦ࢄϞσϧͷόοΫϘʔϯͱͯ͠6/FU͕ଟ༻ • 6/FUͷ.VMUJTDBMFTLJQDPOOFDUJPOTˠ ෆཁͳܭࢉࢿݯͷ༻ 手法 概要 DALL-E 2 [Ramesh+,
22] CLIPを用いてテキストと画像のAlignmentを行う Stable Diffusion [Rombach+, CVPR22] 潜在拡散モデル 6/FU<3POOFCFSHFS .*$$"*> 4UBCMF%JGGVTJPO<3PNCBDI $713>
ఏҊख๏ɿ%JGGVTJPO5SBOTGPSNFS %J5 • જࡏ֦ࢄϞσϧ -%. <3PNCBDI $713>Λϕʔεʹߏங • 7JTJPO5SBOTGPSNFS 7J5
<%PTPWJUTLJZ *$-3>ػߏΛಋೖ • $POEJUJPOJOHʹΑΔ݅ใͷೖྗ
ఏҊख๏ ɿજࡏ֦ࢄϞσϧͱֶͯ͠शͤ͞Δ • ߴ࣍ݩͷըૉۭؒͰ֦ࢄϞσϧΛֶश ͤ͞Δ͜ͱܭࢉྔతʹࠔ • -%.ͱֶͯ͠शͤ͞Δ͜ͱͰ ܭࢉྔΛݮ
• ըૉۭؒͷ֦ࢄϞσϧͰ͋Δ "%.<%IBSJXBM /FVS*14> ͷͷͷ(GMPQTͰֶशՄೳ
ఏҊख๏ ɿೖྗϊΠζΛQBUDIʹղ • "VUPFODPEFS͔ΒಘΒΕͨ /PJTFE-BUFOU YY Λ 7J5ͱಉ༷ʹE࣍ݩͷτʔΫϯ5ʹม •
1BUDIαΠζQΛʹ͢Δͱ5ഒ ʹͳΓUSBOTGPSNFSͷ (GMPQTগͳ͘ͱഒҎ্
ఏҊख๏ ɿ͖݅ೖྗ $POEJUJPOJOH ͷॲཧ • ͖֦݅ࢄϞσϧͰϊΠζΛؚΉը૾ͱͱʹՃใ͕Ճ͑ΒΕΔ FH UJNFTUFQɼΫϥεϥϕϧɼࣗવݴޠ FUD
• ຊݚڀͰ͜ΕΒͷ͖݅ೖྗΛॲཧ͢ΔͨΊʹҎԼͷͭͷҟͳΔઃܭΛఏҊ • *ODPOUFYUDPOEJUJPOJOH • $SPTT"UUFOUJPOCMPDL • "EBQUJWFMBZFSOPSN BEB-/ CMPDL • BEB-/;FSPCMPDL
ఏҊख๏ ɿBEB-/;FSPCMPDL • 7J5ͷTFMGBUUFOUJPOCMPDLʹରͯ͠"EB-/ػߏΛಋೖ • "EB-/ͷεέʔϧ ͓Αͼ ࠩଓͷલͷεέʔϧ
Λύϥϝʔλͱͯ͠Ճ ˠ݅ใΛը૾ʹΑΓڧ͘ө • "EB-/;FSPCMPDLͰͦΕΒΛθϩʹॳظԽ ˠֶशͷॳظஈ֊߃ؔʹ͍ۙಇ͖ ˠ ֶशͷ҆ఆԽ
࣮ݧઃఆ • σʔληοτ • $MBTT$POEJUJPOBM*NBHF/FUY Y<%FOH $713> • ΞʔΩςΫνϟ
• 7J5ͱಉ༷ʹͭͷϞσϧͷେ͖͞ 4 # - 9- Λ༻ҙ • QBUDITJ[FQ • %%1.TBNQMJOHTUFQT • ධՁई • '*% T'*% *4 1SFDJTJPO 3FDBMM • (GMPQT • ֶश • 516WQPE #BUDITJ[F
ఆྔత݁Ռɿ6/FUϕʔεͷख๏Λ্ճͬͨ
ఆੑత݁Ռ • 1BUDITJ[FΛখ͘͞ɼϞσϧΛେ͖͘͢ΔͱΑΓࣗવͳը૾͕ग़ྗ͞ΕΔ ˠ%J5Ͱ(GMPQT͕େ͖͍΄Ͳग़ྗը૾ͷ্࣭͕͕Δ
ࢼ͓ΑͼΤϥʔੳ ఆੑత݁Ռ ɿࣦഊྫ • ಛఆͷMBCFMʹରͯ͠ෆࣗવͳը૾͕ੜ͞ΕΔ • ྫɿJOQVUMBCFM UPZQPPEMF %%1.TBNQMJOHTUFQ
• ϥϕϧʹΑͬͯTUFQͰੜը૾͕ෆ҆ఆˠ ਪ࣌ͷTUFQΛಈతʹมߋ
ॴײ • 4USFOHUI • ֦ࢄϞσϧʹUSBOTGPSNFSΛಋೖ • ܭࢉࢿݯͱग़ྗը૾ͷ࣭ʹ͍ͭͯͷߟ • 8FBLOFTT
• ͕ࣜগͳ͔ͬͨ • Τϥʔੳ͕ͳ͍
·ͱΊ • എܠ • ֦ࢄϞσϧʹΑΔಈը૾ੜ FH 4PSB ͷൃల • ֦ࢄϞσϧʹ͓͚ΔUSBOTGPSNFSͷར༻͕গͳ͍
• ఏҊख๏ • USBOTGPSNFSϕʔεͷ֦ࢄϞσϧͰ͋Δ%JGGVTJPO5SBOTGPSNFS %J5 ΛఏҊ • ݁Ռ • %J5εέʔϥϏϦςΟ͕ߴ͘ɼ(GMPQT͕େ͖͍΄Ͳ'*%͕Լ ˠ ܭࢉࢿݯͱग़ྗը૾ͷ࣭ʹڧ͍૬ؔؔ • %J59-Ϟσϧ͕ɼ$MBTT$POEJUJPOBM*NBHF/FUʹ͓͍ͯ ैདྷͷ6/FUϕʔεͷ֦ࢄϞσϧΛ্ճͬͨ
"QQFOEJYɿ%FOPJTJOH%JGGVTJPO1SPCBCJMJTUJD.PEFM %%1. ֶश
"QQFOEJYɿ$MBTTJGJFSGSFFHVJEBODF • ͖֦݅ࢄϞσϧͰΫϥεϥϕϧΛϥϯμϜʹυϩοϓ ˠ αϯϓϦϯάͷਫ਼Λ্ • #BZFTͷఆཧΑΓ • ֦ࢄϞσϧͷग़ྗΛείΞͱͯ͠ղऍ͢Δͱਪఆ͢ΔϊΠζҎԼͷΑ͏ʹͳΔ
TɿΨΠμϯεεέʔϧ
"QQFOEJYɿ*ODPOUFYUDPOEJUJPOJOH • $POEJUJPOJOHͰ݅ͱͯ͠ೖྗ͞ΕͨτʔΫϯΛ ը૾τʔΫϯͷઌ಄ʹՃ • ͜ΕΒͷτʔΫϯը૾τʔΫϯͱಉ༷ʹѻΘΕɺ 7J5ʣʹ͓͚ΔDMTτʔΫϯͱࣅׂͨΛ࣋ͭ
"QQFOEJYɿ$SPTT"UUFOUJPOCMPDL • 4FMG"UUFOUJPOϒϩοΫͷޙʹ$SPTT"UUFOUJPOΛ Ճͨ͠ઃܭ • <7BTXBOJ /*14>-%.ͱྨࣅͨ͠ΞʔΩςΫνϟ
"QQFOEJYɿ%J5CMPDLEFTJHO • %J59-Ϟσϧʹ͓͍ͯBEB-/;FSPΛ༻͍ͨ ߹͕࠷গͳ͍ܭࢉࢿݯͰ࠷ྑ͍ '*%,είΞΛୡ
"QQFOEJYɿ7JTJPO5SBOTGPSNFS <%PTPWJUTLJZ *$-3>
"QQFOEJYɿ*ODFQUJPO4DPSF *4 • *NBHF/FUͰࣄલֶशࡁΈͷ*ODFQUJPOOFUXPSLΛ༻͍ͨධՁࢦඪ • *ODFQUJPOOFUXPSL͕ࣝผ͘͢͠ɼࣝผ͞ΕΔϥϕϧͷଟ༷ੑ͕͋Δ΄Ͳ େ͖͘ͳΔࢦඪ <4[FHFEZ $713>
"QQFOEJYɿ'SFDIFU*ODFQUJPO%JTUBODF '*% • *NBHF/FUͰࣄલֶशࡁΈͷ*ODFQUJPOOFUXPSLΛ༻͍ͨධՁࢦඪ • ੜ͞Εͨը૾ͷಛ͕(5ը૾ͷಛͱͲͷఔ ࣅ͍ͯΔ͔ΛධՁ͢Δࢦඪ • '*%͕খ͍͞΄Ͳੜ͞Εͨը૾ͷ࣭͕(5ը૾ʹ͍ۙͱߟ͑ΒΕΔ
"QQFOEJYɿ1SFDJTJPO3FDBMM • *NBHF/FUͰࣄલֶशࡁΈͷ7((<4JNPOZBO *$-3>Λ༻͍ͯ ಛϕΫτϧू߹ΛಘΔ
"QQFOEJYɿ(GMPQT • 'MPQTɿුಈখԋࢉͷճ • (GMPQT 'MPQT • ը૾ੜλεΫͰΞʔΩςΫνϟͷෳࡶ͞ΛධՁ͢ΔࡍύϥϝʔλΛ༻͍Δͷ ͕Ұൠత
• ੑೳʹେ͖͘Өڹ͢Δը૾ղ૾ΛҰߟྀ͍ͯ͠ͳ͍ • Ϟσϧͷෳࡶ͞Λද͢ࢦඪͱͯ͠ෆेͳ߹͕͋Δ
"QQFOEJYɿఆྔత݁Ռ
"QQFOEJY(GMPQTͱ'*%ͷ૬ؔ • ΑΓଟ͘ͷ(GMPQTΛͭϞσϧ'*%͕͘ͳΔ
"QQFOEJYɿϞσϧαΠζͱύοναΠζͷݕ౼