activity
20232026
most citedEmu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack

30 citations · 42 across the 16 of their papers we have counts for

collaborators

16 papers

cs.CV2026

Image Generation with a Sphere Encoder

Kaiyu Yue, Menglin Jia, Ji Hou +1

We introduce the Sphere Encoder, an efficient generative framework capable of producing images in a single forward pass and competing with many-step diffusion models using fewer th…

cs.CV2026

HairWeaver: Few-Shot Photorealistic Hair Motion Synthesis with Sim-to-Real Guided Video Diffusion

Di Chang, Ji Hou, Aljaz Bozic +8

We present HairWeaver, a diffusion-based pipeline that animates a single human image with realistic and expressive hair dynamics. While existing methods successfully control body p…

cs.SE2026★ 1 cited

The Llama 4 Herd: Architecture, Training, Evaluation, and Deployment Notes

Redacted by arXiv

This document consolidates publicly reported technical details about Metas Llama 4 model family. It summarizes (i) released variants (Scout and Maverick) and the broader herd conte…

cs.CV2025

Exploring MLLM-Diffusion Information Transfer with MetaCanvas

Han Lin, Xichen Pan, Ziqi Huang +10

Multimodal learning has rapidly advanced visual understanding, largely via multimodal large language models (MLLMs) that use powerful LLMs as cognitive cores. In visual generation,…

cs.CV2025

PhyGDPO: Physics-Aware Groupwise Direct Preference Optimization for Physically Consistent Text-to-Video Generation

Yuanhao Cai, Kunpeng Li, Menglin Jia +11

Recent advances in text-to-video (T2V) generation have achieved good visual quality, yet synthesizing videos that faithfully follow physical laws remains an open challenge. Existin…

cs.CV2025

StreamDiT: Real-Time Streaming Text-to-Video Generation

Akio Kodaira, Tingbo Hou, Ji Hou +4

Recently, great progress has been achieved in text-to-video (T2V) generation by scaling transformer-based diffusion models to billions of parameters, which can generate high-qualit…

cs.CV2025

Token-Shuffle: Towards High-Resolution Image Generation with Autoregressive Models

Xu Ma, Peize Sun, Haoyu Ma +22

Autoregressive (AR) models, long dominant in language generation, are increasingly applied to image synthesis but are often considered less competitive than Diffusion-based models.…

cs.CV2025

Transfer between Modalities with MetaQueries

Xichen Pan, Satya Narayan Shukla, Aashu Singh +9

Unified multimodal models aim to integrate understanding (text output) and generation (pixel output), but aligning these different modalities within a single architecture often dem…

cs.CV2025

MoCha: Towards Movie-Grade Talking Character Synthesis

Cong Wei, Bo Sun, Haoyu Ma +10

Recent advancements in video generation have achieved impressive motion realism, yet they often overlook character-driven storytelling, a crucial task for automated film, animation…

cs.CV2025

Movie Weaver: Tuning-Free Multi-Concept Video Personalization with Anchored Prompts

Feng Liang, Haoyu Ma, Zecheng He +10

Video personalization, which generates customized videos using reference images, has gained significant attention. However, prior methods typically focus on single-concept personal…

cs.CV2024

LinGen: Towards High-Resolution Minute-Length Text-to-Video Generation with Linear Computational Complexity

Hongjie Wang, Chih-Yao Ma, Yen-Cheng Liu +10

Text-to-video generation enhances content creation but is highly computationally intensive: The computational cost of Diffusion Transformers (DiTs) scales quadratically in the numb…

cs.CV2024★ 8 cited

Movie Gen: A Cast of Media Foundation Models

Adam Polyak, Amit Zohar, Andrew Brown +85

We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabili…

cs.CV2024

Pixel-Space Post-Training of Latent Diffusion Models

Christina Zhang, Simran Motwani, Matthew Yu +6

Latent diffusion models (LDMs) have made significant advancements in the field of image generation in recent years. One major advantage of LDMs is their ability to operate in a com…

cs.CV2024★ 3 cited

Cache Me if You Can: Accelerating Diffusion Models through Block Caching

Felix Wimbauer, Bichen Wu, Edgar Schoenfeld +11

Diffusion models have recently revolutionized the field of image synthesis due to their ability to generate photorealistic images. However, one of the major drawbacks of diffusion…

cs.CV2023

ControlRoom3D: Room Generation using Semantic Proxy Rooms

Jonas Schult, Sam Tsai, Lukas Höllein +11

Manually creating 3D environments for AR/VR applications is a complex process requiring expert knowledge in 3D modeling software. Pioneering works facilitate this process by genera…

cs.CV2023★ 30 cited

Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack

Xiaoliang Dai, Ji Hou, Chih-Yao Ma +23

Training text-to-image models with web scale image-text pairs enables the generation of a wide range of visual concepts from text. However, these pre-trained models often face chal…