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20212025
most citedTowards Consistent Video Editing with Text-to-Image Diffusion Models

7 citations · 19 across the 16 of their papers we have counts for

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13 papers · 1 filter

cs.CV2025

Control and Realism: Best of Both Worlds in Layout-to-Image without Training

Bonan Li, Yinhan Hu, Songhua Liu +1

Layout-to-Image generation aims to create complex scenes with precise control over the placement and arrangement of subjects. Existing works have demonstrated that pre-trained Text…

cs.CV2025

Top-Down Compression: Revisit Efficient Vision Token Projection for Visual Instruction Tuning

Bonan li, Zicheng Zhang, Songhua Liu +2

Visual instruction tuning aims to enable large language models to comprehend the visual world, with a pivotal challenge lying in establishing an effective vision-to-language projec…

cs.CV2024

LokiTalk: Learning Fine-Grained and Generalizable Correspondences to Enhance NeRF-based Talking Head Synthesis

Tianqi Li, Ruobing Zheng, Bonan Li +4

Despite significant progress in talking head synthesis since the introduction of Neural Radiance Fields (NeRF), visual artifacts and high training costs persist as major obstacles…

cs.CV2024

DR-BFR: Degradation Representation with Diffusion Models for Blind Face Restoration

Xinmin Qiu, Bonan Li, Zicheng Zhang +2

Blind face restoration (BFR) is fundamentally challenged by the extensive range of degradation types and degrees that impact model generalization. Recent advancements in diffusion…

cs.CV2024★ 1 cited

Focus on Neighbors and Know the Whole: Towards Consistent Dense Multiview Text-to-Image Generator for 3D Creation

Bonan Li, Zicheng Zhang, Xingyi Yang +1

Generating dense multiview images from text prompts is crucial for creating high-fidelity 3D assets. Nevertheless, existing methods struggle with space-view correspondences, result…

cs.CV2024

BlazeBVD: Make Scale-Time Equalization Great Again for Blind Video Deflickering

Xinmin Qiu, Congying Han, Zicheng Zhang +4

Developing blind video deflickering (BVD) algorithms to enhance video temporal consistency, is gaining importance amid the flourish of image processing and video generation. Howeve…

cs.CV2024

Learning Dynamic Tetrahedra for High-Quality Talking Head Synthesis

Zicheng Zhang, Ruobing Zheng, Ziwen Liu +7

Recent works in implicit representations, such as Neural Radiance Fields (NeRF), have advanced the generation of realistic and animatable head avatars from video sequences. These i…

cs.CV2023★ 7 cited

Towards Consistent Video Editing with Text-to-Image Diffusion Models

Zicheng Zhang, Bonan Li, Xuecheng Nie +3

Existing works have advanced Text-to-Image (TTI) diffusion models for video editing in a one-shot learning manner. Despite their low requirements of data and computation, these met…

cs.CV2023★ 1 cited

DiffBFR: Bootstrapping Diffusion Model Towards Blind Face Restoration

Xinmin Qiu, Congying Han, Zicheng Zhang +3

Blind face restoration (BFR) is important while challenging. Prior works prefer to exploit GAN-based frameworks to tackle this task due to the balance of quality and efficiency. Ho…

cs.CV2023★ 2 cited

StyO: Stylize Your Face in Only One-shot

Bonan Li, Zicheng Zhang, Xuecheng Nie +4

This paper focuses on face stylization with a single artistic target. Existing works for this task often fail to retain the source content while achieving geometry variation. Here,…

cs.CV2022★ 1 cited

Masked Reconstruction Contrastive Learning with Information Bottleneck Principle

Ziwen Liu, Bonan Li, Congying Han +2

Contrastive learning (CL) has shown great power in self-supervised learning due to its ability to capture insight correlations among large-scale data. Current CL models are biased…

cs.CV2022★ 3 cited

DropKey

Bonan Li, Yinhan Hu, Xuecheng Nie +4

In this paper, we focus on analyzing and improving the dropout technique for self-attention layers of Vision Transformer, which is important while surprisingly ignored by prior wor…

cs.CV2021

DFS: A Diverse Feature Synthesis Model for Generalized Zero-Shot Learning

Bonan Li, Xuecheng Nie, Congying Han

Generative based strategy has shown great potential in the Generalized Zero-Shot Learning task. However, it suffers severe generalization problem due to lacking of feature diversit…