26 citations · 33 across the 17 of their papers we have counts for
22 papers
SemComp-Bench: Benchmarking Semantic Task Completion in Video Generation
Keyu Tu, Zhuowei Chen, Mengqi Huang +4
We introduce Semantic Task Completion Video Generation, an outcome-oriented video generation task. Under this formulation, success requires both achievement of the intended outcome…
Lance: Unified Multimodal Modeling by Multi-Task Synergy
Fengyi Fu, Mengqi Huang, Shaojin Wu +10
We present Lance, a lightweight native unified model supporting multimodal understanding, generation, and editing for both images and videos. Rather than relying on model capacity…
Stream-T1: Test-Time Scaling for Streaming Video Generation
Yijing Tu, Shaojin Wu, Mengqi Huang +4
While Test-Time Scaling (TTS) offers a promising direction to enhance video generation without the surging costs of training, current test-time video generation methods based on di…
NativeTok: Native Visual Tokenization for Improved Image Generation
Bin Wu, Mengqi Huang, Weinan Jia +1
VQ-based image generation typically follows a two-stage pipeline: a tokenizer encodes images into discrete tokens, and a generative model learns their dependencies for reconstructi…
LayerEdit: Disentangled Multi-Object Editing via Conflict-Aware Multi-Layer Learning
Fengyi Fu, Mengqi Huang, Lei Zhang +1
Text-driven multi-object image editing which aims to precisely modify multiple objects within an image based on text descriptions, has recently attracted considerable interest. Exi…
MoGA: Mixture-of-Groups Attention for End-to-End Long Video Generation
Weinan Jia, Yuning Lu, Mengqi Huang +6
Long video generation with Diffusion Transformers (DiTs) is bottlenecked by the quadratic scaling of full attention with sequence length. Since attention is highly redundant, outpu…
LongAnimation: Long Animation Generation with Dynamic Global-Local Memory
Nan Chen, Mengqi Huang, Yihao Meng +1
Animation colorization is a crucial part of real animation industry production. Long animation colorization has high labor costs. Therefore, automated long animation colorization b…
Pro3D-Editor : A Progressive-Views Perspective for Consistent and Precise 3D Editing
Yang Zheng, Mengqi Huang, Nan Chen +1
Text-guided 3D editing aims to precisely edit semantically relevant local 3D regions, which has significant potential for various practical applications ranging from 3D games to fi…
HDGlyph: A Hierarchical Disentangled Glyph-Based Framework for Long-Tail Text Rendering in Diffusion Models
Shuhan Zhuang, Mengqi Huang, Fengyi Fu +3
Visual text rendering, which aims to accurately integrate specified textual content within generated images, is critical for various applications such as commercial design. Despite…
DualReal: Adaptive Joint Training for Lossless Identity-Motion Fusion in Video Customization
Wenchuan Wang, Mengqi Huang, Yijing Tu +1
Customized text-to-video generation with pre-trained large-scale models has recently garnered significant attention by focusing on identity and motion consistency. Existing works t…
DiT: Dynamic Diffusion Transformer for Accurate Image Generation
Weinan Jia, Mengqi Huang, Nan Chen +2
Diffusion models are widely recognized for their ability to generate high-fidelity images. Despite the excellent performance and scalability of the Diffusion Transformer (DiT) arch…
Less-to-More Generalization: Unlocking More Controllability by In-Context Generation
Shaojin Wu, Mengqi Huang, Wenxu Wu +3
Although subject-driven generation has been extensively explored in image generation due to its wide applications, it still has challenges in data scalability and subject expansibi…
RealGeneral: Unifying Visual Generation via Temporal In-Context Learning with Video Models
Yijing Lin, Mengqi Huang, Shuhan Zhuang +1
Unifying diverse image generation tasks within a single framework remains a fundamental challenge in visual generation. While large language models (LLMs) achieve unification throu…
VMix: Improving Text-to-Image Diffusion Model with Cross-Attention Mixing Control
Shaojin Wu, Fei Ding, Mengqi Huang +2
While diffusion models show extraordinary talents in text-to-image generation, they may still fail to generate highly aesthetic images. More specifically, there is still a gap betw…
CustomContrast: A Multilevel Contrastive Perspective For Subject-Driven Text-to-Image Customization
Nan Chen, Mengqi Huang, Zhuowei Chen +3
Subject-driven text-to-image (T2I) customization has drawn significant interest in academia and industry. This task enables pre-trained models to generate novel images based on uni…
RealCustom++: Representing Images as Real Textual Word for Real-Time Customization
Zhendong Mao, Mengqi Huang, Fei Ding +3
Given a text and an image of a specific subject, text-to-image customization aims to generate new images that align with both the text and the subject's appearance. Existing works…
RealCustom: Narrowing Real Text Word for Real-Time Open-Domain Text-to-Image Customization
Mengqi Huang, Zhendong Mao, Mingcong Liu +2
Text-to-image customization, which aims to synthesize text-driven images for the given subjects, has recently revolutionized content creation. Existing works follow the pseudo-word…
Gradual Residuals Alignment: A Dual-Stream Framework for GAN Inversion and Image Attribute Editing
Hao Li, Mengqi Huang, Lei Zhang +3
GAN-based image attribute editing firstly leverages GAN Inversion to project real images into the latent space of GAN and then manipulates corresponding latent codes. Recent invers…
DreamIdentity: Improved Editability for Efficient Face-identity Preserved Image Generation
Zhuowei Chen, Shancheng Fang, Wei Liu +4
While large-scale pre-trained text-to-image models can synthesize diverse and high-quality human-centric images, an intractable problem is how to preserve the face identity for con…
Not All Image Regions Matter: Masked Vector Quantization for Autoregressive Image Generation
Mengqi Huang, Zhendong Mao, Quan Wang +1
Existing autoregressive models follow the two-stage generation paradigm that first learns a codebook in the latent space for image reconstruction and then completes the image gener…
Towards Accurate Image Coding: Improved Autoregressive Image Generation with Dynamic Vector Quantization
Mengqi Huang, Zhendong Mao, Zhuowei Chen +1
Existing vector quantization (VQ) based autoregressive models follow a two-stage generation paradigm that first learns a codebook to encode images as discrete codes, and then compl…
DSE-GAN: Dynamic Semantic Evolution Generative Adversarial Network for Text-to-Image Generation
Mengqi Huang, Zhendong Mao, Penghui Wang +2
Text-to-image generation aims at generating realistic images which are semantically consistent with the given text. Previous works mainly adopt the multi-stage architecture by stac…