activity
20162025
most citedLearning Linear Transformations for Fast Arbitrary Style Transfer

95 citations · 702 across the 43 of their papers we have counts for

collaborators

46 papers

cs.CV2025

Synthesizing Consistent Novel Views via 3D Epipolar Attention without Re-Training

Botao Ye, Sifei Liu, Xueting Li +2

Large diffusion models demonstrate remarkable zero-shot capabilities in novel view synthesis from a single image. However, these models often face challenges in maintaining consist…

cs.CV2024

No Pose, No Problem: Surprisingly Simple 3D Gaussian Splats from Sparse Unposed Images

Botao Ye, Sifei Liu, Haofei Xu +4

We introduce NoPoSplat, a feed-forward model capable of reconstructing 3D scenes parameterized by 3D Gaussians from \textit{unposed} sparse multi-view images. Our model, trained ex…

cs.CV2023★ 2 cited

COLMAP-Free 3D Gaussian Splatting

Yang Fu, Sifei Liu, Amey Kulkarni +3

While neural rendering has led to impressive advances in scene reconstruction and novel view synthesis, it relies heavily on accurately pre-computed camera poses. To relax this con…

cs.CV2023★ 1 cited

A Unified Approach for Text- and Image-guided 4D Scene Generation

Yufeng Zheng, Xueting Li, Koki Nagano +4

Large-scale diffusion generative models are greatly simplifying image, video and 3D asset creation from user-provided text prompts and images. However, the challenging problem of t…

cs.CV2023★ 2 cited

3D Reconstruction with Generalizable Neural Fields using Scene Priors

Yang Fu, Shalini De Mello, Xueting Li +4

High-fidelity 3D scene reconstruction has been substantially advanced by recent progress in neural fields. However, most existing methods train a separate network from scratch for…

cs.CV2023★ 7 cited

Generalizable One-shot Neural Head Avatar

Xueting Li, Shalini De Mello, Sifei Liu +3

We present a method that reconstructs and animates a 3D head avatar from a single-view portrait image. Existing methods either involve time-consuming optimization for a specific pe…

cs.CV2023★ 1 cited

Zero-shot Pose Transfer for Unrigged Stylized 3D Characters

Jiashun Wang, Xueting Li, Sifei Liu +4

Transferring the pose of a reference avatar to stylized 3D characters of various shapes is a fundamental task in computer graphics. Existing methods either require the stylized cha…

cs.CV2023★ 2 cited

TUVF: Learning Generalizable Texture UV Radiance Fields

An-Chieh Cheng, Xueting Li, Sifei Liu +1

Textures are a vital aspect of creating visually appealing and realistic 3D models. In this paper, we study the problem of generating high-fidelity texture given shapes of 3D asset…

cs.CV2023★ 11 cited

Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models

Jiarui Xu, Sifei Liu, Arash Vahdat +3

We present ODISE: Open-vocabulary DIffusion-based panoptic SEgmentation, which unifies pre-trained text-image diffusion and discriminative models to perform open-vocabulary panopti…

cs.CV2023★ 2 cited

Affordance Diffusion: Synthesizing Hand-Object Interactions

Yufei Ye, Xueting Li, Abhinav Gupta +5

Recent successes in image synthesis are powered by large-scale diffusion models. However, most methods are currently limited to either text- or image-conditioned generation for syn…

cs.CV2022

Physics-based Indirect Illumination for Inverse Rendering

Youming Deng, Xueting Li, Sifei Liu +1

We present a physics-based inverse rendering method that learns the illumination, geometry, and materials of a scene from posed multi-view RGB images. To model the illumination of…

cs.CV2022

Autoregressive 3D Shape Generation via Canonical Mapping

An-Chieh Cheng, Xueting Li, Sifei Liu +2

With the capacity of modeling long-range dependencies in sequential data, transformers have shown remarkable performances in a variety of generative tasks such as image, audio, and…

cs.CV2022

CoordGAN: Self-Supervised Dense Correspondences Emerge from GANs

Jiteng Mu, Shalini De Mello, Zhiding Yu +4

Recent advances show that Generative Adversarial Networks (GANs) can synthesize images with smooth variations along semantically meaningful latent directions, such as pose, express…

cs.CV2022★ 12 cited

GroupViT: Semantic Segmentation Emerges from Text Supervision

Jiarui Xu, Shalini De Mello, Sifei Liu +4

Grouping and recognition are important components of visual scene understanding, e.g., for object detection and semantic segmentation. With end-to-end deep learning systems, groupi…

cs.CV2021★ 5 cited

Learning Continuous Environment Fields via Implicit Functions

Xueting Li, Shalini De Mello, Xiaolong Wang +3

We propose a novel scene representation that encodes reaching distance -- the distance between any position in the scene to a goal along a feasible trajectory. We demonstrate that…

cs.CV2021

Self-Supervised Object Detection via Generative Image Synthesis

Siva Karthik Mustikovela, Shalini De Mello, Aayush Prakash +5

We present SSOD, the first end-to-end analysis-by synthesis framework with controllable GANs for the task of self-supervised object detection. We use collections of real world imag…

cs.CV2021

Video Autoencoder: self-supervised disentanglement of static 3D structure and motion

Zihang Lai, Sifei Liu, Alexei A. Efros +1

A video autoencoder is proposed for learning disentan- gled representations of 3D structure and camera pose from videos in a self-supervised manner. Relying on temporal continuity…

cs.CV2021

Learning Contrastive Representation for Semantic Correspondence

Taihong Xiao, Sifei Liu, Shalini De Mello +3

Dense correspondence across semantically related images has been extensively studied, but still faces two challenges: 1) large variations in appearance, scale and pose exist even f…

cs.CV2021★ 14 cited

Learning 3D Dense Correspondence via Canonical Point Autoencoder

An-Chieh Cheng, Xueting Li, Min Sun +2

We propose a canonical point autoencoder (CPAE) that predicts dense correspondences between 3D shapes of the same category. The autoencoder performs two key functions: (a) encoding…

cs.CV2021★ 2 cited

Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Time

Shaowei Liu, Hanwen Jiang, Jiarui Xu +2

Estimating 3D hand and object pose from a single image is an extremely challenging problem: hands and objects are often self-occluded during interactions, and the 3D annotations ar…

cs.CV2021★ 18 cited

Contrastive Syn-to-Real Generalization

Wuyang Chen, Zhiding Yu, Shalini De Mello +4

Training on synthetic data can be beneficial for label or data-scarce scenarios. However, synthetically trained models often suffer from poor generalization in real domains due to…

cs.CV2021★ 3 cited

Learning to Track Instances without Video Annotations

Yang Fu, Sifei Liu, Umar Iqbal +3

Tracking segmentation masks of multiple instances has been intensively studied, but still faces two fundamental challenges: 1) the requirement of large-scale, frame-wise annotation…

cs.CV2020★ 19 cited

Online Adaptation for Consistent Mesh Reconstruction in the Wild

Xueting Li, Sifei Liu, Shalini De Mello +4

This paper presents an algorithm to reconstruct temporally consistent 3D meshes of deformable object instances from videos in the wild. Without requiring annotations of 3D mesh, 2D…

cs.CV2020★ 33 cited

Learning Continuous Image Representation with Local Implicit Image Function

Yinbo Chen, Sifei Liu, Xiaolong Wang

How to represent an image? While the visual world is presented in a continuous manner, machines store and see the images in a discrete way with 2D arrays of pixels. In this paper,…