17 citations · 20 across the 14 of their papers we have counts for
16 papers
Diagnose-to-Generate: Eliminating Structural Distortions in Flow Models via Patch-Level Grounded Alignment
Yifan Li, Lishuai Gao, Tong Zhang +8
Flow-based image generators achieve strong semantic synthesis but still produce localized structural distortions, such as malformed hands and limbs. Existing post-training methods…
On incremental and semi-global exponential stability of gradient flows satisfying generalized Łojasiewicz inequalities
Andreas Oliveira, Arthur C. B. de Oliveira, Mario Sznaier +1
The Łojasiewicz inequality characterizes objective-value convergence along gradient flows and, in special cases, yields exponential decay of the cost. However, such results do not…
Forge-and-Quench: Enhancing Image Generation for Higher Fidelity in Unified Multimodal Models
Yanbing Zeng, Jia Wang, Hanghang Ma +4
Integrating image generation and understanding into a single framework has become a pivotal goal in the multimodal domain. However, how understanding can effectively assist generat…
MagicMirror: A Large-Scale Dataset and Benchmark for Fine-Grained Artifacts Assessment in Text-to-Image Generation
Jia Wang, Jie Hu, Xiaoqi Ma +3
Text-to-image (T2I) generation has achieved remarkable progress in instruction following and aesthetics. However, a persistent challenge is the prevalence of physical artifacts, su…
Omni-Dish: Photorealistic and Faithful Image Generation and Editing for Arbitrary Chinese Dishes
Huijie Liu, Bingcan Wang, Jie Hu +2
Dish images play a crucial role in the digital era, with the demand for culturally distinctive dish images continuously increasing due to the digitization of the food industry and…
Image Editing with Diffusion Models: A Survey
Jia Wang, Jie Hu, Xiaoqi Ma +3
With deeper exploration of diffusion model, developments in the field of image generation have triggered a boom in image creation. As the quality of base-model generated images con…
Separate Motion from Appearance: Customizing Motion via Customizing Text-to-Video Diffusion Models
Huijie Liu, Jingyun Wang, Shuai Ma +3
Motion customization aims to adapt the diffusion model (DM) to generate videos with the motion specified by a set of video clips with the same motion concept. To realize this goal,…
RDPM: Solve Diffusion Probabilistic Models via Recurrent Token Prediction
Xiaoping Wu, Jie Hu, Xiaoming Wei
Diffusion Probabilistic Models (DPMs) have emerged as the de facto approach for high-fidelity image synthesis, operating diffusion processes on continuous VAE latent, which signifi…
High-Resolution Image Synthesis via Next-Token Prediction
Dengsheng Chen, Jie Hu, Tiezhu Yue +2
Recently, autoregressive models have demonstrated remarkable performance in class-conditional image generation. However, the application of next-token prediction to high-resolution…
Denoising with a Joint-Embedding Predictive Architecture
Dengsheng Chen, Jie Hu, Xiaoming Wei +1
Joint-embedding predictive architectures (JEPAs) have shown substantial promise in self-supervised representation learning, yet their application in generative modeling remains und…
Kangaroo: A Powerful Video-Language Model Supporting Long-context Video Input
Jiajun Liu, Yibing Wang, Hanghang Ma +6
Rapid advancements have been made in extending Large Language Models (LLMs) to Large Multi-modal Models (LMMs). However, extending input modality of LLMs to video data remains a ch…
Fine-gained Zero-shot Video Sampling
Dengsheng Chen, Jie Hu, Xiaoming Wei +1
Incorporating a temporal dimension into pretrained image diffusion models for video generation is a prevalent approach. However, this method is computationally demanding and necess…
Deformable 3D Shape Diffusion Model
Dengsheng Chen, Jie Hu, Xiaoming Wei +1
The Gaussian diffusion model, initially designed for image generation, has recently been adapted for 3D point cloud generation. However, these adaptations have not fully considered…
Orthogonal Temporal Interpolation for Zero-Shot Video Recognition
Yan Zhu, Junbao Zhuo, Bin Ma +4
Zero-shot video recognition (ZSVR) is a task that aims to recognize video categories that have not been seen during the model training process. Recently, vision-language models (VL…
Rethinking skip connection model as a learnable Markov chain
Dengsheng Chen, Jie Hu, Wenwen Qiang +2
Over past few years afterward the birth of ResNet, skip connection has become the defacto standard for the design of modern architectures due to its widespread adoption, easy optim…
Large Scale Visual Food Recognition
Weiqing Min, Zhiling Wang, Yuxin Liu +5
Food recognition plays an important role in food choice and intake, which is essential to the health and well-being of humans. It is thus of importance to the computer vision commu…