311 citations · 783 across the 19 of their papers we have counts for
19 papers
InstaRevive: One-Step Image Enhancement via Dynamic Score Matching
Yixuan Zhu, Haolin Wang, Ao Li +6
Image enhancement finds wide-ranging applications in real-world scenarios due to complex environments and the inherent limitations of imaging devices. Recent diffusion-based method…
DiffMoE: Dynamic Token Selection for Scalable Diffusion Transformers
Minglei Shi, Ziyang Yuan, Haotian Yang +10
Diffusion models have demonstrated remarkable success in various image generation tasks, but their performance is often limited by the uniform processing of inputs across varying c…
FlowTurbo: Towards Real-time Flow-Based Image Generation with Velocity Refiner
Wenliang Zhao, Minglei Shi, Xumin Yu +2
Building on the success of diffusion models in visual generation, flow-based models reemerge as another prominent family of generative models that have achieved competitive or bett…
DC-Solver: Improving Predictor-Corrector Diffusion Sampler via Dynamic Compensation
Wenliang Zhao, Haolin Wang, Jie Zhou +1
Diffusion probabilistic models (DPMs) have shown remarkable performance in visual synthesis but are computationally expensive due to the need for multiple evaluations during the sa…
FlowIE: Efficient Image Enhancement via Rectified Flow
Yixuan Zhu, Wenliang Zhao, Ao Li +3
Image enhancement holds extensive applications in real-world scenarios due to complex environments and limitations of imaging devices. Conventional methods are often constrained by…
DPMesh: Exploiting Diffusion Prior for Occluded Human Mesh Recovery
Yixuan Zhu, Ao Li, Yansong Tang +3
The recovery of occluded human meshes presents challenges for current methods due to the difficulty in extracting effective image features under severe occlusion. In this paper, we…
OpenVoice: Versatile Instant Voice Cloning
Zengyi Qin, Wenliang Zhao, Xumin Yu +1
We introduce OpenVoice, a versatile voice cloning approach that requires only a short audio clip from the reference speaker to replicate their voice and generate speech in multiple…
Unleashing Text-to-Image Diffusion Models for Visual Perception
Wenliang Zhao, Yongming Rao, Zuyan Liu +3
Diffusion models (DMs) have become the new trend of generative models and have demonstrated a powerful ability of conditional synthesis. Among those, text-to-image diffusion models…
UniPC: A Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models
Wenliang Zhao, Lujia Bai, Yongming Rao +2
Diffusion probabilistic models (DPMs) have demonstrated a very promising ability in high-resolution image synthesis. However, sampling from a pre-trained DPM is time-consuming due…
DiffTalk: Crafting Diffusion Models for Generalized Audio-Driven Portraits Animation
Shuai Shen, Wenliang Zhao, Zibin Meng +4
Talking head synthesis is a promising approach for the video production industry. Recently, a lot of effort has been devoted in this research area to improve the generation quality…
HorNet: Efficient High-Order Spatial Interactions with Recursive Gated Convolutions
Yongming Rao, Wenliang Zhao, Yansong Tang +3
Recent progress in vision Transformers exhibits great success in various tasks driven by the new spatial modeling mechanism based on dot-product self-attention. In this paper, we s…
Dynamic Spatial Sparsification for Efficient Vision Transformers and Convolutional Neural Networks
Yongming Rao, Zuyan Liu, Wenliang Zhao +2
In this paper, we present a new approach for model acceleration by exploiting spatial sparsity in visual data. We observe that the final prediction in vision Transformers is only b…
A Roadmap for Big Model
Sha Yuan, Hanyu Zhao, Shuai Zhao +97
With the rapid development of deep learning, training Big Models (BMs) for multiple downstream tasks becomes a popular paradigm. Researchers have achieved various outcomes in the c…
DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting
Yongming Rao, Wenliang Zhao, Guangyi Chen +5
Recent progress has shown that large-scale pre-training using contrastive image-text pairs can be a promising alternative for high-quality visual representation learning from natur…
Group-aware Contrastive Regression for Action Quality Assessment
Xumin Yu, Yongming Rao, Wenliang Zhao +2
Assessing action quality is challenging due to the subtle differences between videos and large variations in scores. Most existing approaches tackle this problem by regressing a qu…
Towards Interpretable Deep Metric Learning with Structural Matching
Wenliang Zhao, Yongming Rao, Ziyi Wang +2
How do the neural networks distinguish two images? It is of critical importance to understand the matching mechanism of deep models for developing reliable intelligent systems for…
Global Filter Networks for Image Classification
Yongming Rao, Wenliang Zhao, Zheng Zhu +2
Recent advances in self-attention and pure multi-layer perceptrons (MLP) models for vision have shown great potential in achieving promising performance with fewer inductive biases…
DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification
Yongming Rao, Wenliang Zhao, Benlin Liu +3
Attention is sparse in vision transformers. We observe the final prediction in vision transformers is only based on a subset of most informative tokens, which is sufficient for acc…
Field-weighted Factorization Machines for Click-Through Rate Prediction in Display Advertising
Junwei Pan, Jian Xu, Alfonso Lobos Ruiz +4
Click-through rate (CTR) prediction is a critical task in online display advertising. The data involved in CTR prediction are typically multi-field categorical data, i.e., every fe…