1.9k citations · 2k across the 11 of their papers we have counts for
11 papers
Efficient-VQGAN: Towards High-Resolution Image Generation with Efficient Vision Transformers
Shiyue Cao, Yueqin Yin, Lianghua Huang +4
Vector-quantized image modeling has shown great potential in synthesizing high-quality images. However, generating high-resolution images remains a challenging task due to the quad…
AnyDoor: Zero-shot Object-level Image Customization
Xi Chen, Lianghua Huang, Yu Liu +3
This work presents AnyDoor, a diffusion-based image generator with the power to teleport target objects to new scenes at user-specified locations in a harmonious way. Instead of tu…
Lipschitz Singularities in Diffusion Models
Zhantao Yang, Ruili Feng, Han Zhang +8
Diffusion models, which employ stochastic differential equations to sample images through integrals, have emerged as a dominant class of generative models. However, the rationality…
Composer: Creative and Controllable Image Synthesis with Composable Conditions
Lianghua Huang, Di Chen, Yu Liu +3
Recent large-scale generative models learned on big data are capable of synthesizing incredible images yet suffer from limited controllability. This work offers a new generation pa…
Dimensionality-Varying Diffusion Process
Han Zhang, Ruili Feng, Zhantao Yang +7
Diffusion models, which learn to reverse a signal destruction process to generate new data, typically require the signal at each step to have the same dimension. We argue that, con…
DiffGAR: Model-Agnostic Restoration from Generative Artifacts Using Image-to-Image Diffusion Models
Yueqin Yin, Lianghua Huang, Yu Liu +1
Recent generative models show impressive results in photo-realistic image generation. However, artifacts often inevitably appear in the generated results, leading to downgraded use…
Global Instance Tracking: Locating Target More Like Humans
Shiyu Hu, Xin Zhao, Lianghua Huang +1
Target tracking, the essential ability of the human visual system, has been simulated by computer vision tasks. However, existing trackers perform well in austere experimental envi…
Self-supervised Video Representation Learning by Context and Motion Decoupling
Lianghua Huang, Yu Liu, Bin Wang +3
A key challenge in self-supervised video representation learning is how to effectively capture motion information besides context bias. While most existing works implicitly achieve…
Train a One-Million-Way Instance Classifier for Unsupervised Visual Representation Learning
Yu Liu, Lianghua Huang, Pan Pan +3
This paper presents a simple unsupervised visual representation learning method with a pretext task of discriminating all images in a dataset using a parametric, instance-level cla…
GlobalTrack: A Simple and Strong Baseline for Long-term Tracking
Lianghua Huang, Xin Zhao, Kaiqi Huang
A key capability of a long-term tracker is to search for targets in very large areas (typically the entire image) to handle possible target absences or tracking failures. However,…
GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wild
Lianghua Huang, Xin Zhao, Kaiqi Huang
We introduce here a large tracking database that offers an unprecedentedly wide coverage of common moving objects in the wild, called GOT-10k. Specifically, GOT-10k is built upon t…