210 citations · 1.2k across the 58 of their papers we have counts for
59 papers · 1 filter
Simplifying and Improving On-Policy Distillation for Few-Step Diffusion
Jiawei Zhang, Ziyu Wan, Nanye Ma +5
Few-step distillation reduces the sampling cost of diffusion and flow models, but existing approaches often require auxiliary score models or specialized architectures. We show tha…
LACON: Training Text-to-Image Model from Uncurated Data
Zhiyang Liang, Ziyu Wan, Hongyu Liu +4
The success of modern text-to-image generation is largely attributed to massive, high-quality datasets. Currently, these datasets are curated through a filter-first paradigm that a…
SmartEraser: Remove Anything from Images using Masked-Region Guidance
Longtao Jiang, Zhendong Wang, Jianmin Bao +5
Object removal has so far been dominated by the mask-and-inpaint paradigm, where the masked region is excluded from the input, leaving models relying on unmasked areas to inpaint t…
PersonMAE: Person Re-Identification Pre-Training with Masked AutoEncoders
Hezhen Hu, Xiaoyi Dong, Jianmin Bao +4
Pre-training is playing an increasingly important role in learning generic feature representation for Person Re-identification (ReID). We argue that a high-quality ReID representat…
Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior
Junshu Tang, Tengfei Wang, Bo Zhang +4
In this work, we investigate the problem of creating high-fidelity 3D content from only a single image. This is inherently challenging: it essentially involves estimating the under…
CiCo: Domain-Aware Sign Language Retrieval via Cross-Lingual Contrastive Learning
Yiting Cheng, Fangyun Wei, Jianmin Bao +2
This work focuses on sign language retrieval-a recently proposed task for sign language understanding. Sign language retrieval consists of two sub-tasks: text-to-sign-video (T2V) r…
IRGen: Generative Modeling for Image Retrieval
Yidan Zhang, Ting Zhang, Dong Chen +11
While generative modeling has become prevalent across numerous research fields, its integration into the realm of image retrieval remains largely unexplored and underjustified. In…
Efficient Diffusion Training via Min-SNR Weighting Strategy
Tiankai Hang, Shuyang Gu, Chen Li +5
Denoising diffusion models have been a mainstream approach for image generation, however, training these models often suffers from slow convergence. In this paper, we discovered th…
CLIP Itself is a Strong Fine-tuner: Achieving 85.7% and 88.0% Top-1 Accuracy with ViT-B and ViT-L on ImageNet
Xiaoyi Dong, Jianmin Bao, Ting Zhang +7
Recent studies have shown that CLIP has achieved remarkable success in performing zero-shot inference while its fine-tuning performance is not satisfactory. In this paper, we ident…
Rodin: A Generative Model for Sculpting 3D Digital Avatars Using Diffusion
Tengfei Wang, Bo Zhang, Ting Zhang +8
This paper presents a 3D generative model that uses diffusion models to automatically generate 3D digital avatars represented as neural radiance fields. A significant challenge in…
MetaPortrait: Identity-Preserving Talking Head Generation with Fast Personalized Adaptation
Bowen Zhang, Chenyang Qi, Pan Zhang +6
In this work, we propose an ID-preserving talking head generation framework, which advances previous methods in two aspects. First, as opposed to interpolating from sparse flow, we…
X-Paste: Revisiting Scalable Copy-Paste for Instance Segmentation using CLIP and StableDiffusion
Hanqing Zhao, Dianmo Sheng, Jianmin Bao +9
Copy-Paste is a simple and effective data augmentation strategy for instance segmentation. By randomly pasting object instances onto new background images, it creates new training…
Paint by Example: Exemplar-based Image Editing with Diffusion Models
Binxin Yang, Shuyang Gu, Bo Zhang +5
Language-guided image editing has achieved great success recently. In this paper, for the first time, we investigate exemplar-guided image editing for more precise control. We achi…
3DFaceShop: Explicitly Controllable 3D-Aware Portrait Generation
Junshu Tang, Bo Zhang, Binxin Yang +4
In contrast to the traditional avatar creation pipeline which is a costly process, contemporary generative approaches directly learn the data distribution from photographs. While p…
DigiFace-1M: 1 Million Digital Face Images for Face Recognition
Gwangbin Bae, Martin de La Gorce, Tadas Baltrusaitis +5
State-of-the-art face recognition models show impressive accuracy, achieving over 99.8% on Labeled Faces in the Wild (LFW) dataset. Such models are trained on large-scale datasets…
Bootstrapped Masked Autoencoders for Vision BERT Pretraining
Xiaoyi Dong, Jianmin Bao, Ting Zhang +6
We propose bootstrapped masked autoencoders (BootMAE), a new approach for vision BERT pretraining. BootMAE improves the original masked autoencoders (MAE) with two core designs: 1)…
Semantic Image Synthesis via Diffusion Models
Wengang Zhou, Weilun Wang, Jianmin Bao +4
Denoising Diffusion Probabilistic Models (DDPMs) have achieved remarkable success in various image generation tasks compared with Generative Adversarial Nets (GANs). Recent work on…
I^2R-Net: Intra- and Inter-Human Relation Network for Multi-Person Pose Estimation
Yiwei Ding, Wenjin Deng, Yinglin Zheng +6
In this paper, we present the Intra- and Inter-Human Relation Networks (I^2R-Net) for Multi-Person Pose Estimation. It involves two basic modules. First, the Intra-Human Relation M…
Pretraining is All You Need for Image-to-Image Translation
Tengfei Wang, Ting Zhang, Bo Zhang +4
We propose to use pretraining to boost general image-to-image translation. Prior image-to-image translation methods usually need dedicated architectural design and train individual…
Improved Vector Quantized Diffusion Models
Zhicong Tang, Shuyang Gu, Jianmin Bao +2
Vector quantized diffusion (VQ-Diffusion) is a powerful generative model for text-to-image synthesis, but sometimes can still generate low-quality samples or weakly correlated imag…
Contrastive Learning Rivals Masked Image Modeling in Fine-tuning via Feature Distillation
Yixuan Wei, Han Hu, Zhenda Xie +5
Masked image modeling (MIM) learns representations with remarkably good fine-tuning performances, overshadowing previous prevalent pre-training approaches such as image classificat…
Real-Time Neural Character Rendering with Pose-Guided Multiplane Images
Hao Ouyang, Bo Zhang, Pan Zhang +5
We propose pose-guided multiplane image (MPI) synthesis which can render an animatable character in real scenes with photorealistic quality. We use a portable camera rig to capture…
Protecting Celebrities from DeepFake with Identity Consistency Transformer
Xiaoyi Dong, Jianmin Bao, Dongdong Chen +6
In this work we propose Identity Consistency Transformer, a novel face forgery detection method that focuses on high-level semantics, specifically identity information, and detecti…
Large-Scale Pre-training for Person Re-identification with Noisy Labels
Dengpan Fu, Dongdong Chen, Hao Yang +6
This paper aims to address the problem of pre-training for person re-identification (Re-ID) with noisy labels. To setup the pre-training task, we apply a simple online multi-object…