Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

Introducing Diffusion Forcing, which unifies next-token prediction (eg LLMs) and full-seq. diffusion (eg SORA)! It offers improved performance & new sampling strategies in vision and robotics, such as stable, infinite video generation, better diffusion planning, and more! (1/8)

BoyuanChen0's profile picture

Boyuan Chen

12,417 subscribers

208,434 görüntüleme • 1 yıl önce •via X (Twitter)

Bilim & Teknoloji
LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models "Block diffusion sequentially generates blocks of tokens by performing diffusion within each block and conditioning on previous blocks. By combining strength from autoregressive and diffusion models, block diffusion overcomes the limitations of both approaches by supporting variable-length, higher-quality generation and improving inference efficiency with KV caching and parallel sampling."
0:19

Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models "Block diffusion sequentially generates blocks of tokens by performing diffusion within each block and conditioning on previous blocks. By combining strength from autoregressive and diffusion models, block diffusion overcomes the limitations of both approaches by supporting variable-length, higher-quality generation and improving inference efficiency with KV caching and parallel sampling."

Tanishq Mathew Abraham, Ph.D.

21,813 görüntüleme • 1 yıl önce

Stochastic and deterministic sampling strategies for diffusion models produce strikingly different trajectories, but both ultimately achieve the same aim. I had a great time presenting our work, Diffusion Explorer, this week at IEEE VIS in Vienna.
0:14

Stochastic and deterministic sampling strategies for diffusion models produce strikingly different trajectories, but both ultimately achieve the same aim. I had a great time presenting our work, Diffusion Explorer, this week at IEEE VIS in Vienna.

Alec Helbling

279,017 görüntüleme • 7 ay önce

generative 3D heads in Blender with Stable Diffusion, ControlNet and FaceBuilder
0:10

generative 3D heads in Blender with Stable Diffusion, ControlNet and FaceBuilder

dmvrg

181,770 görüntüleme • 2 yıl önce

You can build your own AI-apps powered by OpenAI and Stable Diffusion. **Even if you don't know how to code** Using no-code, build your own text and image generation apps with: - Bubble - OpenAI - Stable Diffusion Learn how:
0:12

You can build your own AI-apps powered by OpenAI and Stable Diffusion. **Even if you don't know how to code** Using no-code, build your own text and image generation apps with: - Bubble - OpenAI - Stable Diffusion Learn how:

Seth Kramer

6,893,639 görüntüleme • 3 yıl önce

DimensionX: Create Any 3D and 4D Scenes from a Single Image with Controllable Video Diffusion TL;DR: Create 3/4DGS from Video Diffusion Note: Some first inference code released (not all yet). Contributions (cited): • We present DimensionX, a novel framework for generating photorealistic 3D and 4D scenes from only a single image using controllable video diffusion. • We propose ST-Director, which decouples the spatial and temporal priors in video diffusion models by learning (spatial and temporal) dimension-aware modules with our curated datasets. We further enhance the hybriddimension control with a training-free composition approach according to the essence of video diffusion denoising process. • To bridge the gap between video diffusion and real-world scenes, we design a trajectory-aware mechanism for 3D generation and an identity-preserving denoising approach for 4D generation, enabling more realistic and controllable scene synthesis. • Extensive experiments manifest that our DimensionX delivers superior performance in video, 3D, and 4D generation compared with baseline methods.
0:18

DimensionX: Create Any 3D and 4D Scenes from a Single Image with Controllable Video Diffusion TL;DR: Create 3/4DGS from Video Diffusion Note: Some first inference code released (not all yet). Contributions (cited): • We present DimensionX, a novel framework for generating photorealistic 3D and 4D scenes from only a single image using controllable video diffusion. • We propose ST-Director, which decouples the spatial and temporal priors in video diffusion models by learning (spatial and temporal) dimension-aware modules with our curated datasets. We further enhance the hybriddimension control with a training-free composition approach according to the essence of video diffusion denoising process. • To bridge the gap between video diffusion and real-world scenes, we design a trajectory-aware mechanism for 3D generation and an identity-preserving denoising approach for 4D generation, enabling more realistic and controllable scene synthesis. • Extensive experiments manifest that our DimensionX delivers superior performance in video, 3D, and 4D generation compared with baseline methods.

MrNeRF

17,017 görüntüleme • 1 yıl önce

🚨Announcing our #ICLR2025 Oral! 🔥Diffusion LMs are on the rise for parallel text generation! But unlike autoregressive LMs, they struggle with quality, fixed-length constraints & lack of KV caching. 🚀Introducing Block Diffusion—combining autoregressive and diffusion models for the best of both worlds! 👇1/7
0:17

🚨Announcing our #ICLR2025 Oral! 🔥Diffusion LMs are on the rise for parallel text generation! But unlike autoregressive LMs, they struggle with quality, fixed-length constraints & lack of KV caching. 🚀Introducing Block Diffusion—combining autoregressive and diffusion models for the best of both worlds! 👇1/7

Marianne Arriola

148,147 görüntüleme • 1 yıl önce

Made this cool AI Vid with AnimateDiff and Inpainting with Stable Diffusion!
0:18

Made this cool AI Vid with AnimateDiff and Inpainting with Stable Diffusion!

Aleksej Lotkov

550,072 görüntüleme • 2 yıl önce

Diffusions are excellent in creating fantastic images and videos 🔎 We cooked a *diffusion* model to synthesize structured data #ICLR2025 🔥 Introducing TabDiff, a mixed-type diffusion model for generating synthetic tabular data, imputing missing values, and beyond! 🧵 1/n
0:15

Diffusions are excellent in creating fantastic images and videos 🔎 We cooked a *diffusion* model to synthesize structured data #ICLR2025 🔥 Introducing TabDiff, a mixed-type diffusion model for generating synthetic tabular data, imputing missing values, and beyond! 🧵 1/n

Minkai Xu

50,434 görüntüleme • 1 yıl önce

MMaDA-Parallel Multimodal Large Diffusion Language Models for Thinking-Aware Editing and Generation
0:16

MMaDA-Parallel Multimodal Large Diffusion Language Models for Thinking-Aware Editing and Generation

AK

66,111 görüntüleme • 6 ay önce

🚨New paper! Generative models are often “miscalibrated”. We calibrate diffusion models, LLMs, and more to meet desired distributional properties. E.g. we finetune protein models to better match the diversity of natural proteins.
0:10

🚨New paper! Generative models are often “miscalibrated”. We calibrate diffusion models, LLMs, and more to meet desired distributional properties. E.g. we finetune protein models to better match the diversity of natural proteins.

Brian L Trippe

20,445 görüntüleme • 8 ay önce

Meta presents MarDini Masked Autoregressive Diffusion for Video Generation at Scale
0:16

Meta presents MarDini Masked Autoregressive Diffusion for Video Generation at Scale

AK

70,051 görüntüleme • 1 yıl önce

DreamPose: Fashion Image-to-Video Synthesis via Stable Diffusion abs: project page: github:
0:16

DreamPose: Fashion Image-to-Video Synthesis via Stable Diffusion abs: project page: github:

AK

152,818 görüntüleme • 3 yıl önce

Today, we are adding Stable Video Diffusion, our foundation model for generative video to the Stability AI Developer Platform API. The model can generate 2 seconds of video, comprising of 25 generated frames and 24 frames of FILM interpolation, within an average time of 41 seconds. Developers interested in utilizing Stable Video Diffusion through an API can access it now on the Stability AI Developer Platform. Learn more here:
0:18

Today, we are adding Stable Video Diffusion, our foundation model for generative video to the Stability AI Developer Platform API. The model can generate 2 seconds of video, comprising of 25 generated frames and 24 frames of FILM interpolation, within an average time of 41 seconds. Developers interested in utilizing Stable Video Diffusion through an API can access it now on the Stability AI Developer Platform. Learn more here:

Stability AI

175,571 görüntüleme • 2 yıl önce

You can now use Flux and other image generation models for free on PUBLC, including: - Flux.1 Schnell & Flux.1 Dev by Black Forest Labs - Stable Diffusion 3 by Stability AI - SDXL-Lightning-4Step by ByteDance Unleash your creativity✨ Try it now -
0:14

You can now use Flux and other image generation models for free on PUBLC, including: - Flux.1 Schnell & Flux.1 Dev by Black Forest Labs - Stable Diffusion 3 by Stability AI - SDXL-Lightning-4Step by ByteDance Unleash your creativity✨ Try it now -

PUBLC

648,867 görüntüleme • 1 yıl önce

Show-o One Single Transformer to Unify Multimodal Understanding and Generation discuss: We present a unified transformer, i.e., Show-o, that unifies multimodal understanding and generation. Unlike fully autoregressive models, Show-o unifies autoregressive and (discrete) diffusion modeling to adaptively handle inputs and outputs of various and mixed modalities. The unified model flexibly supports a wide range of vision-language tasks including visual question-answering, text-to-image generation, text-guided inpainting/extrapolation, and mixed-modality generation. Across various benchmarks, it demonstrates comparable or superior performance to existing individual models with an equivalent or larger number of parameters tailored for understanding or generation. This significantly highlights its potential as a next-generation foundation model.
0:13

Show-o One Single Transformer to Unify Multimodal Understanding and Generation discuss: We present a unified transformer, i.e., Show-o, that unifies multimodal understanding and generation. Unlike fully autoregressive models, Show-o unifies autoregressive and (discrete) diffusion modeling to adaptively handle inputs and outputs of various and mixed modalities. The unified model flexibly supports a wide range of vision-language tasks including visual question-answering, text-to-image generation, text-guided inpainting/extrapolation, and mixed-modality generation. Across various benchmarks, it demonstrates comparable or superior performance to existing individual models with an equivalent or larger number of parameters tailored for understanding or generation. This significantly highlights its potential as a next-generation foundation model.

AK

124,040 görüntüleme • 1 yıl önce

Dang, I just can't get over how good this Stable Video Diffusion model is.
0:18

Dang, I just can't get over how good this Stable Video Diffusion model is.

fofr

141,884 görüntüleme • 2 yıl önce

(1/2) Check out "𝐏𝐨𝐥𝐲𝐃𝐢𝐟𝐟: Generating 3D Polygonal Meshes with Diffusion Models"! Our model operates directly on the polygons of 3D meshes and generates novel shapes as output through an iterative diffusion process.
0:11

(1/2) Check out "𝐏𝐨𝐥𝐲𝐃𝐢𝐟𝐟: Generating 3D Polygonal Meshes with Diffusion Models"! Our model operates directly on the polygons of 3D meshes and generates novel shapes as output through an iterative diffusion process.

Matthias Niessner

57,912 görüntüleme • 2 yıl önce

LLaDA (the first Large Language Diffusion Model) is *just* out 💥 and I've built a demo, try out now 👨‍💻 It's mesmerizing to watch the diffusion process 🌀, and it being a diffusion model gives you superpowers like "the 4th word has to be pineapple" 🦸 Demo and weights 👇
0:17

LLaDA (the first Large Language Diffusion Model) is *just* out 💥 and I've built a demo, try out now 👨‍💻 It's mesmerizing to watch the diffusion process 🌀, and it being a diffusion model gives you superpowers like "the 4th word has to be pineapple" 🦸 Demo and weights 👇

apolinario (poli)

82,599 görüntüleme • 1 yıl önce

here friends! let's all learn about stable diffusion together! ✨
0:15

here friends! let's all learn about stable diffusion together! ✨

MoFoxxies

21,443 görüntüleme • 6 ay önce