Metaverse 2.0.
— Robert Scoble (@Scobleizer) 16 juin 2023
Your avatar will be animated. https://t.co/STqGvYxZBQ
Metaverse 2.0. Your avatar will be animated.
MULTIMODAL AI
-
Metaverse 2.0: Animated Avatars Technology Evolution
By
–
-
Amazement at cellular imagery reveals biological complexity
By
–
The more images of our cells I see the more amazed I am.
-
Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale
By
–
Voicebox: Text-Guided Multilingual Universal Speech Generation at Scale
— AK (@_akhaliq) 16 juin 2023
blog: https://t.co/cw89vKIAUK
Large-scale generative models such as GPT and DALL-E have revolutionized natural language processing and computer vision research. These models not only generate high fidelity… pic.twitter.com/vkHyOEvpVBVoicebox: Text-Guided Multilingual Universal Speech Generation at Scale blog:
https://ai.facebook.com/blog/voicebox-generative-ai-model-speech/
… Large-scale generative models such as GPT and DALL-E have revolutionized natural language processing and computer vision research. These models not only generate high fidelity -
Zero-Shot Text-Guided Video-to-Video Translation Framework
By
–
AI video to video translation
— AK (@_akhaliq) 16 juin 2023
demo: https://t.co/3aQwySFFT4
Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translation
paper proposes a novel zero-shot text-guided video-to-video translation framework to adapt image models to videos. The framework includes two parts:… pic.twitter.com/P8ERsMf6NUAI video to video translation demo: https://
huggingface.co/spaces/Anonymo
us-sub/Rerender
… Rerender A Video: Zero-Shot Text-Guided Video-to-Video Translation paper proposes a novel zero-shot text-guided video-to-video translation framework to adapt image models to videos. The framework includes two parts: -
NAVI: High-Quality 3D Shape and Pose Annotations for Images
By
–
NAVI: Category-Agnostic Image Collections with High-Quality 3D Shape and Pose Annotations paper page: https://
huggingface.co/papers/2306.09
109
… Recent advances in neural reconstruction enable high-quality 3D object reconstruction from casually captured image collections. Current techniques -
iPhone Audio Recognition: Hearing Groups in Noisy Environments
By
–
Can listen to a group and get everything even if iPhone is two feet away in a noisy room.
-
DreamHuman: Generate Animatable 3D Avatars from Text
By
–
DreamHuman: Animatable 3D Avatars from Text
— AK (@_akhaliq) 16 juin 2023
paper page: https://t.co/w3dnN9wS6o
present DreamHuman, a method to generate realistic animatable 3D human avatar models solely from textual descriptions. Recent text-to-3D methods have made considerable strides in generation, but are… pic.twitter.com/HpsWFJnsxrDreamHuman: Animatable 3D Avatars from Text paper page: https://
huggingface.co/papers/2306.09
329
… present DreamHuman, a method to generate realistic animatable 3D human avatar models solely from textual descriptions. Recent text-to-3D methods have made considerable strides in generation, but are -
Neural Relighting with Subsurface Scattering via Radiance Transfer
By
–
Neural Relighting with Subsurface Scattering by Learning the Radiance Transfer Gradient paper page: https://
huggingface.co/papers/2306.09
322
… Reconstructing and relighting objects and scenes under varying lighting conditions is challenging: existing neural rendering methods often cannot handle -
Diffusion Models for Zero-Shot Open-Vocabulary Segmentation
By
–
Diffusion Models for Zero-Shot Open-Vocabulary Segmentation
— AK (@_akhaliq) 16 juin 2023
paper page: https://t.co/JP6BymlyTs
The variety of objects in the real world is nearly unlimited and is thus impossible to capture using models trained on a fixed set of categories. As a result, in recent years,… pic.twitter.com/BVI1gSpjRnDiffusion Models for Zero-Shot Open-Vocabulary Segmentation paper page: https://
huggingface.co/papers/2306.09
316
… The variety of objects in the real world is nearly unlimited and is thus impossible to capture using models trained on a fixed set of categories. As a result, in recent years, -
TryOnDiffusion: Virtual Garment Try-On Using Dual UNet Architecture
By
–
TryOnDiffusion: A Tale of Two UNets
— AK (@_akhaliq) 16 juin 2023
paper page: https://t.co/SuDRe7rqQD
Given two images depicting a person and a garment worn by another person, our goal is to generate a visualization of how the garment might look on the input person. A key challenge is to synthesize a… pic.twitter.com/qcIXtUbqyLTryOnDiffusion: A Tale of Two UNets paper page: https://
huggingface.co/papers/2306.08
276
… Given two images depicting a person and a garment worn by another person, our goal is to generate a visualization of how the garment might look on the input person. A key challenge is to synthesize a