87 citations · 719 across the 60 of their papers we have counts for
60 papers
BerfScene: Bev-conditioned Equivariant Radiance Fields for Infinite 3D Scene Generation
Qihang Zhang, Yinghao Xu, Yujun Shen +3
Generating large-scale 3D scenes cannot simply apply existing 3D object synthesis technique since 3D scenes usually hold complex spatial configurations and consist of a number of o…
In-Domain GAN Inversion for Faithful Reconstruction and Editability
Jiapeng Zhu, Yujun Shen, Yinghao Xu +3
Generative Adversarial Networks (GANs) have significantly advanced image synthesis through mapping randomly sampled latent codes to high-fidelity synthesized images. However, apply…
Exploring Sparse MoE in GANs for Text-conditioned Image Synthesis
Jiapeng Zhu, Ceyuan Yang, Kecheng Zheng +3
Due to the difficulty in scaling up, generative adversarial networks (GANs) seem to be falling from grace on the task of text-conditioned image synthesis. Sparsely-activated mixtur…
Learning Modulated Transformation in GANs
Ceyuan Yang, Qihang Zhang, Yinghao Xu +3
The success of style-based generators largely benefits from style modulation, which helps take care of the cross-instance variation within data. However, the instance-wise stochast…
Regularized Mask Tuning: Uncovering Hidden Knowledge in Pre-trained Vision-Language Models
Kecheng Zheng, Wei Wu, Ruili Feng +6
Prompt tuning and adapter tuning have shown great potential in transferring pre-trained vision-language models (VLMs) to various downstream tasks. In this work, we design a new typ…
CoDeF: Content Deformation Fields for Temporally Consistent Video Processing
Hao Ouyang, Qiuyu Wang, Yuxi Xiao +6
We present the content deformation field CoDeF as a new type of video representation, which consists of a canonical content field aggregating the static contents in the entire vide…
AnyDoor: Zero-shot Object-level Image Customization
Xi Chen, Lianghua Huang, Yu Liu +3
This work presents AnyDoor, a diffusion-based image generator with the power to teleport target objects to new scenes at user-specified locations in a harmonious way. Instead of tu…
Benchmarking and Analyzing 3D-aware Image Synthesis with a Modularized Codebase
Qiuyu Wang, Zifan Shi, Kecheng Zheng +3
Despite the rapid advance of 3D-aware image synthesis, existing studies usually adopt a mixture of techniques and tricks, leaving it unclear how each part contributes to the final…
VideoComposer: Compositional Video Synthesis with Motion Controllability
Xiang Wang, Hangjie Yuan, Shiwei Zhang +6
The pursuit of controllability as a higher standard of visual content creation has yielded remarkable progress in customizable image synthesis. However, achieving controllable vide…
Balancing Logit Variation for Long-tailed Semantic Segmentation
Yuchao Wang, Jingjing Fei, Haochen Wang +5
Semantic segmentation usually suffers from a long-tail data distribution. Due to the imbalanced number of samples across categories, the features of those tail classes may get sque…
Lipschitz Singularities in Diffusion Models
Zhantao Yang, Ruili Feng, Han Zhang +8
Diffusion models, which employ stochastic differential equations to sample images through integrals, have emerged as a dominant class of generative models. However, the rationality…
Using Unreliable Pseudo-Labels for Label-Efficient Semantic Segmentation
Haochen Wang, Yuchao Wang, Yujun Shen +3
The crux of label-efficient semantic segmentation is to produce high-quality pseudo-labels to leverage a large amount of unlabeled or weakly labeled data. A common practice is to s…
Cones 2: Customizable Image Synthesis with Multiple Subjects
Zhiheng Liu, Yifei Zhang, Yujun Shen +7
Synthesizing images with user-specified subjects has received growing attention due to its practical applications. Despite the recent success in single subject customization, exist…
Pulling Target to Source: A New Perspective on Domain Adaptive Semantic Segmentation
Haochen Wang, Yujun Shen, Jingjing Fei +4
Domain adaptive semantic segmentation aims to transfer knowledge from a labeled source domain to an unlabeled target domain. However, existing methods primarily focus on directly l…
Revisiting the Evaluation of Image Synthesis with GANs
Mengping Yang, Ceyuan Yang, Yichi Zhang +3
A good metric, which promises a reliable comparison between solutions, is essential for any well-defined task. Unlike most vision tasks that have per-sample ground-truth, image syn…
Scanning Only Once: An End-to-end Framework for Fast Temporal Grounding in Long Videos
Yulin Pan, Xiangteng He, Biao Gong +4
Video temporal grounding aims to pinpoint a video segment that matches the query description. Despite the recent advance in short-form videos (\textit{e.g.}, in minutes), temporal…
ViM: Vision Middleware for Unified Downstream Transferring
Yutong Feng, Biao Gong, Jianwen Jiang +4
Foundation models are pre-trained on massive data and transferred to downstream tasks via fine-tuning. This work presents Vision Middleware (ViM), a new learning paradigm that targ…
VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation
Zhengxiong Luo, Dayou Chen, Yingya Zhang +6
A diffusion probabilistic model (DPM), which constructs a forward diffusion process by gradually adding noise to data points and learns the reverse denoising process to generate ne…
Composer: Creative and Controllable Image Synthesis with Composable Conditions
Lianghua Huang, Di Chen, Yu Liu +3
Recent large-scale generative models learned on big data are capable of synthesizing incredible images yet suffer from limited controllability. This work offers a new generation pa…
UKnow: A Unified Knowledge Protocol with Multimodal Knowledge Graph Datasets for Reasoning and Vision-Language Pre-Training
Biao Gong, Shuai Tan, Yutong Feng +6
This work presents a unified knowledge protocol, called UKnow, which facilitates knowledge-based studies from the perspective of data. Particularly focusing on visual and linguisti…
GH-Feat: Learning Versatile Generative Hierarchical Features from GANs
Yinghao Xu, Yujun Shen, Jiapeng Zhu +2
Recent years witness the tremendous success of generative adversarial networks (GANs) in synthesizing photo-realistic images. GAN generator learns to compose realistic images and r…
Spatial Steerability of GANs via Self-Supervision from Discriminator
Jianyuan Wang, Lalit Bhagat, Ceyuan Yang +4
Generative models make huge progress to the photorealistic image synthesis in recent years. To enable human to steer the image generation process and customize the output, many wor…
Learning 3D-aware Image Synthesis with Unknown Pose Distribution
Zifan Shi, Yujun Shen, Yinghao Xu +5
Existing methods for 3D-aware image synthesis largely depend on the 3D pose distribution pre-estimated on the training set. An inaccurate estimation may mislead the model into lear…
LinkGAN: Linking GAN Latents to Pixels for Controllable Image Synthesis
Jiapeng Zhu, Ceyuan Yang, Yujun Shen +4
This work presents an easy-to-use regularizer for GAN training, which helps explicitly link some axes of the latent space to a set of pixels in the synthesized image. Establishing…