85 citations · 187 across the 18 of their papers we have counts for
19 papers
Universal Adversarial Purification with DDIM Metric Loss for Stable Diffusion
Li Zheng, Liangbin Xie, Jiantao Zhou +1
Stable Diffusion (SD) often produces degraded outputs when the training dataset contains adversarial noise. Adversarial purification offers a promising solution by removing adversa…
SimpleGVR: A Simple Baseline for Latent-Cascaded Video Super-Resolution
Liangbin Xie, Yu Li, Shian Du +7
Latent diffusion models have emerged as a leading paradigm for efficient video generation. However, as user expectations shift toward higher-resolution outputs, relying solely on l…
VideoPainter: Any-length Video Inpainting and Editing with Plug-and-Play Context Control
Yuxuan Bian, Zhaoyang Zhang, Xuan Ju +4
Video inpainting, which aims to restore corrupted video content, has experienced substantial progress. Despite these advances, existing methods, whether propagating unmasked region…
Lumina-OmniLV: A Unified Multimodal Framework for General Low-Level Vision
Yuandong Pu, Le Zhuo, Kaiwen Zhu +7
We present Lunima-OmniLV (abbreviated as OmniLV), a universal multimodal multi-task framework for low-level vision that addresses over 100 sub-tasks across four major categories: i…
TurboFill: Adapting Few-step Text-to-image Model for Fast Image Inpainting
Liangbin Xie, Daniil Pakhomov, Zhonghao Wang +8
This paper introduces TurboFill, a fast image inpainting model that enhances a few-step text-to-image diffusion model with an inpainting adapter for high-quality and efficient inpa…
Anti-Diffusion: Preventing Abuse of Modifications of Diffusion-Based Models
Zheng Li, Liangbin Xie, Jiantao Zhou +3
Although diffusion-based techniques have shown remarkable success in image generation and editing tasks, their abuse can lead to severe negative social impacts. Recently, some work…
Image Conductor: Precision Control for Interactive Video Synthesis
Yaowei Li, Xintao Wang, Zhaoyang Zhang +5
Filmmaking and animation production often require sophisticated techniques for coordinating camera transitions and object movements, typically involving labor-intensive real-world…
SmartEdit: Exploring Complex Instruction-based Image Editing with Multimodal Large Language Models
Yuzhou Huang, Liangbin Xie, Xintao Wang +8
Current instruction-based editing methods, such as InstructPix2Pix, often fail to produce satisfactory results in complex scenarios due to their dependence on the simple CLIP text…
StyleAdapter: A Unified Stylized Image Generation Model
Zhouxia Wang, Xintao Wang, Liangbin Xie +4
This work focuses on generating high-quality images with specific style of reference images and content of provided textual descriptions. Current leading algorithms, i.e., DreamBoo…
DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models
Liangbin Xie, Xintao Wang, Xiangyu Chen +4
Image super-resolution (SR) with generative adversarial networks (GAN) has achieved great success in restoring realistic details. However, it is notorious that GAN-based SR models…
T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models
Chong Mou, Xintao Wang, Liangbin Xie +5
The incredible generative ability of large-scale text-to-image (T2I) models has demonstrated strong power of learning complex structures and meaningful semantics. However, relying…
Mitigating Artifacts in Real-World Video Super-Resolution Models
Liangbin Xie, Xintao Wang, Shuwei Shi +3
The recurrent structure is a prevalent framework for the task of video super-resolution, which models the temporal dependency between frames via hidden states. When applied to real…
Rethinking Alignment in Video Super-Resolution Transformers
Shuwei Shi, Jinjin Gu, Liangbin Xie +3
The alignment of adjacent frames is considered an essential operation in video super-resolution (VSR). Advanced VSR models, including the latest VSR Transformers, are generally equ…
VFHQ: A High-Quality Dataset and Benchmark for Video Face Super-Resolution
Liangbin Xie. Xintao Wang, Honglun Zhang, Chao Dong +1
Most of the existing video face super-resolution (VFSR) methods are trained and evaluated on VoxCeleb1, which is designed specifically for speaker identification and the frames in…
VQFR: Blind Face Restoration with Vector-Quantized Dictionary and Parallel Decoder
Yuchao Gu, Xintao Wang, Liangbin Xie +4
Although generative facial prior and geometric prior have recently demonstrated high-quality results for blind face restoration, producing fine-grained facial details faithful to i…
NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results
Ren Yang, Radu Timofte, Meisong Zheng +75
This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the…
Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data
Xintao Wang, Liangbin Xie, Chao Dong +1
Though many attempts have been made in blind super-resolution to restore low-resolution images with unknown and complex degradations, they are still far from addressing general rea…
Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution
Liangbin Xie, Xintao Wang, Chao Dong +2
Recent blind super-resolution (SR) methods typically consist of two branches, one for degradation prediction and the other for conditional restoration. However, our experiments sho…
Enhanced Quadratic Video Interpolation
Yihao Liu, Liangbin Xie, Li Siyao +3
With the prosperity of digital video industry, video frame interpolation has arisen continuous attention in computer vision community and become a new upsurge in industry. Many lea…