7 citations · 19 across the 16 of their papers we have counts for
17 papers
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…
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…
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…
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…
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…
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…
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…
General Method for Solving Four Types of SAT Problems
Anqi Li, Congying Han, Tiande Guo +2
Existing methods provide varying algorithms for different types of Boolean satisfiability problems (SAT), lacking a general solution framework. Accordingly, this study proposes a u…
A-PSRO: A Unified Strategy Learning Method with Advantage Function for Normal-form Games
Yudong Hu, Haoran Li, Congying Han +3
Solving Nash equilibrium is the key challenge in normal-form games with large strategy spaces, where open-ended learning frameworks offer an efficient approach. In this work, we pr…
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…
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…
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,…
Generating Linear programming Instances with Controllable Rank and Condition Number
Anqi Li, Congying Han, Tiande Guo
Instances generation is crucial for linear programming algorithms, which is necessary either to find the optimal pivot rules by training learning method or to evaluate and verify c…
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…
On the optimal pivot path of simplex method for linear programming based on reinforcement learning
Anqi Li, Tiande Guo, Congying Han +2
Based on the existing pivot rules, the simplex method for linear programming is not polynomial in the worst case. Therefore the optimal pivot of the simplex method is crucial. This…
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…
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…