Search Results for author: Xingyi Yang

Found 46 papers, 26 papers with code

Test3R: Learning to Reconstruct 3D at Test Time

1 code implementation16 Jun 2025 Yuheng Yuan, Qiuhong Shen, Shizun Wang, Xingyi Yang, Xinchao Wang

Extensive experiments demonstrate that our technique significantly outperforms previous state-of-the-art methods on the 3D reconstruction and multi-view depth estimation tasks.

3D Reconstruction Depth Estimation

Minute-Long Videos with Dual Parallelisms

1 code implementation27 May 2025 Zeqing Wang, Bowen Zheng, Xingyi Yang, Zhenxiong Tan, Yuecong Xu, Xinchao Wang

Diffusion Transformer (DiT)-based video diffusion models generate high-quality videos at scale but incur prohibitive processing latency and memory costs for long videos.

Denoising Video Generation

1000+ FPS 4D Gaussian Splatting for Dynamic Scene Rendering

no code implementations20 Mar 2025 Yuheng Yuan, Qiuhong Shen, Xingyi Yang, Xinchao Wang

(Q1) \textbf{Short-Lifespan Gaussians}: 4DGS uses a large portion of Gaussians with short temporal span to represent scene dynamics, leading to an excessive number of Gaussians.

OminiControl2: Efficient Conditioning for Diffusion Transformers

1 code implementation11 Mar 2025 Zhenxiong Tan, Qiaochu Xue, Xingyi Yang, Songhua Liu, Xinchao Wang

Fine-grained control of text-to-image diffusion transformer models (DiT) remains a critical challenge for practical deployment.

Conditional Image Generation Denoising

Efficient Gaussian Splatting for Monocular Dynamic Scene Rendering via Sparse Time-Variant Attribute Modeling

no code implementations27 Feb 2025 Hanyang Kong, Xingyi Yang, Xinchao Wang

In response, we introduce Efficient Dynamic Gaussian Splatting (EDGS), which represents dynamic scenes via sparse time-variant attribute modeling.

Attribute

GraphBridge: Towards Arbitrary Transfer Learning in GNNs

1 code implementation26 Feb 2025 Li Ju, Xingyi Yang, Qi Li, Xinchao Wang

Empirical validation, conducted over 16 datasets representative of these scenarios, confirms the framework's capacity for task- and domain-agnostic transfer learning within graph-like data, marking a significant advancement in the field of GNNs.

Transfer Learning

Generative Sparse-View Gaussian Splatting

no code implementations CVPR 2025 Hanyang Kong, Xingyi Yang, Xinchao Wang

Novel view synthesis from limited observations remains a significant challenge due to the lack of information in under-sampled regions, often resulting in noticeable artifacts.

Novel View Synthesis

CoSER: Towards Consistent Dense Multiview Text-to-Image Generator for 3D Creation

no code implementations CVPR 2025 Bonan Li, ZiCheng Zhang, Xingyi Yang, Xinchao Wang

To further enhance cross-view consistency and alleviate content drift, CoSER rapidly scan all views in spiral bidirectional manner to aware holistic information and then scores each point based on semantic material.

3D Generation Text to 3D

AdvAnchor: Enhancing Diffusion Model Unlearning with Adversarial Anchors

no code implementations28 Dec 2024 Mengnan Zhao, Lihe Zhang, Xingyi Yang, Tianhang Zheng, BaoCai Yin

In this paper, we systematically analyze the impact of diverse text anchors on unlearning performance.

model

OminiControl: Minimal and Universal Control for Diffusion Transformer

2 code implementations22 Nov 2024 Zhenxiong Tan, Songhua Liu, Xingyi Yang, Qiaochu Xue, Xinchao Wang

In this paper, we introduce OminiControl, a highly versatile and parameter-efficient framework that integrates image conditions into pre-trained Diffusion Transformer (DiT) models.

Vista3D: Unravel the 3D Darkside of a Single Image

1 code implementation18 Sep 2024 Qiuhong Shen, Xingyi Yang, Michael Bi Mi, Xinchao Wang

We embark on the age-old quest: unveiling the hidden dimensions of objects from mere glimpses of their visible parts.

3D Generation Diversity

Kolmogorov-Arnold Transformer

1 code implementation16 Sep 2024 Xingyi Yang, Xinchao Wang

In this paper, we introduce the Kolmogorov-Arnold Transformer (KAT), a novel architecture that replaces MLP layers with Kolmogorov-Arnold Network (KAN) layers to enhance the expressiveness and performance of the model.

Image Classification

FlashSplat: 2D to 3D Gaussian Splatting Segmentation Solved Optimally

1 code implementation12 Sep 2024 Qiuhong Shen, Xingyi Yang, Xinchao Wang

Extensive experiments demonstrate the efficiency and robustness of our method in segmenting various scenes, and its superior performance in downstream tasks such as object removal and inpainting.

Focus on Neighbors and Know the Whole: Towards Consistent Dense Multiview Text-to-Image Generator for 3D Creation

no code implementations23 Aug 2024 Bonan Li, ZiCheng Zhang, Xingyi Yang, Xinchao Wang

To further enhance cross-view consistency and alleviate content drift, CoSER rapidly scan all views in spiral bidirectional manner to aware holistic information and then scores each point based on semantic material.

3D Generation Text to 3D

Video-Infinity: Distributed Long Video Generation

no code implementations24 Jun 2024 Zhenxiong Tan, Xingyi Yang, Songhua Liu, Xinchao Wang

Specifically, we propose two coherent mechanisms: Clip parallelism and Dual-scope attention.

Video Generation

Compositional Video Generation as Flow Equalization

1 code implementation10 Jun 2024 Xingyi Yang, Xinchao Wang

Despite the promising results, a significant challenge remains: these models struggle to fully grasp complex compositional interactions between multiple concepts and actions.

Video Editing Video Generation

GFlow: Recovering 4D World from Monocular Video

no code implementations28 May 2024 Shizun Wang, Xingyi Yang, Qiuhong Shen, Zhenxiang Jiang, Xinchao Wang

To solve this, we introduce GFlow, a new framework that utilizes only 2D priors (depth and optical flow) to lift a video to a 4D scene, as a flow of 3D Gaussians through space and time.

4D reconstruction Novel View Synthesis +1

Hash3D: Training-free Acceleration for 3D Generation

1 code implementation CVPR 2025 Xingyi Yang, Xinchao Wang

The evolution of 3D generative modeling has been notably propelled by the adoption of 2D diffusion models.

3D Generation Image to 3D +1

Unsegment Anything by Simulating Deformation

1 code implementation CVPR 2024 Jiahao Lu, Xingyi Yang, Xinchao Wang

Foundation segmentation models, while powerful, pose a significant risk: they enable users to effortlessly extract any objects from any digital content with a single click, potentially leading to copyright infringement or malicious misuse.

Segmentation

Relation Rectification in Diffusion Model

no code implementations CVPR 2024 Yinwei Wu, Xingyi Yang, Xinchao Wang

Despite their exceptional generative abilities, large text-to-image diffusion models, much like skilled but careless artists, often struggle with accurately depicting visual relationships between objects.

model Relation

SG-Former: Self-guided Transformer with Evolving Token Reallocation

1 code implementation ICCV 2023 Sucheng Ren, Xingyi Yang, Songhua Liu, Xinchao Wang

At the heart of our approach is to utilize a significance map, which is estimated through hybrid-scale self-attention and evolves itself during training, to reallocate tokens based on the significance of each region.

Diffusion Model as Representation Learner

1 code implementation ICCV 2023 Xingyi Yang, Xinchao Wang

In this paper, we conduct an in-depth investigation of the representation power of DPMs, and propose a novel knowledge transfer method that leverages the knowledge acquired by generative DPMs for recognition tasks.

Denoising image-classification +5

Distribution Shift Inversion for Out-of-Distribution Prediction

1 code implementation CVPR 2023 Runpeng Yu, Songhua Liu, Xingyi Yang, Xinchao Wang

Machine learning society has witnessed the emergence of a myriad of Out-of-Distribution (OoD) algorithms, which address the distribution shift between the training and the testing distribution by searching for a unified predictor or invariant feature representation.

Domain Generalization Prediction

Anything-3D: Towards Single-view Anything Reconstruction in the Wild

1 code implementation19 Apr 2023 Qiuhong Shen, Xingyi Yang, Xinchao Wang

3D reconstruction from a single-RGB image in unconstrained real-world scenarios presents numerous challenges due to the inherent diversity and complexity of objects and environments.

3D Reconstruction Diversity +1

Diffusion Probabilistic Model Made Slim

no code implementations CVPR 2023 Xingyi Yang, Daquan Zhou, Jiashi Feng, Xinchao Wang

Despite the recent visually-pleasing results achieved, the massive computational cost has been a long-standing flaw for diffusion probabilistic models (DPMs), which, in turn, greatly limits their applications on resource-limited platforms.

Image Generation model +1

Dataset Factorization for Condensation

1 code implementation NIPS 2022 Songhua Liu, Kai Wang, Xingyi Yang, Jingwen Ye, Xinchao Wang

In this paper, we study dataset distillation (DD), from a novel perspective and introduce a \emph{dataset factorization} approach, termed \emph{HaBa}, which is a plug-and-play strategy portable to any existing DD baseline.

Dataset Distillation Diversity +2

Dataset Distillation via Factorization

3 code implementations30 Oct 2022 Songhua Liu, Kai Wang, Xingyi Yang, Jingwen Ye, Xinchao Wang

In this paper, we study \xw{dataset distillation (DD)}, from a novel perspective and introduce a \emph{dataset factorization} approach, termed \emph{HaBa}, which is a plug-and-play strategy portable to any existing DD baseline.

Dataset Distillation Hallucination +1

Deep Model Reassembly

1 code implementation24 Oct 2022 Xingyi Yang, Daquan Zhou, Songhua Liu, Jingwen Ye, Xinchao Wang

Given a collection of heterogeneous models pre-trained from distinct sources and with diverse architectures, the goal of DeRy, as its name implies, is to first dissect each model into distinctive building blocks, and then selectively reassemble the derived blocks to produce customized networks under both the hardware resource and performance constraints.

model Transfer Learning

Learning with Recoverable Forgetting

1 code implementation17 Jul 2022 Jingwen Ye, Yifang Fu, Jie Song, Xingyi Yang, Songhua Liu, Xin Jin, Mingli Song, Xinchao Wang

Life-long learning aims at learning a sequence of tasks without forgetting the previously acquired knowledge.

General Knowledge Transfer Learning

Factorizing Knowledge in Neural Networks

1 code implementation4 Jul 2022 Xingyi Yang, Jingwen Ye, Xinchao Wang

The core idea of KF lies in the modularization and assemblability of knowledge: given a pretrained network model as input, KF aims to decompose it into several factor networks, each of which handles only a dedicated task and maintains task-specific knowledge factorized from the source network.

Disentanglement Transfer Learning

Neural Point Process for Learning Spatiotemporal Event Dynamics

1 code implementation12 Dec 2021 ZiHao Zhou, Xingyi Yang, Ryan Rossi, Handong Zhao, Rose Yu

The key construction of our approach is the nonparametric space-time intensity function, governed by a latent process.

Point Processes Variational Inference

Neural Point Process for Forecasting Spatiotemporal Events

no code implementations1 Jan 2021 ZiHao Zhou, Xingyi Yang, Xinyi He, Ryan Rossi, Handong Zhao, Rose Yu

To the best of our knowledge, this is the first neural point process model that can jointly predict both the space and time of events.

Density Estimation Point Processes

Stochastic Gradient Variance Reduction by Solving a Filtering Problem

1 code implementation22 Dec 2020 Xingyi Yang

Deep neural networks (DNN) are typically optimized using stochastic gradient descent (SGD).

Stochastic Optimization

DSRNA: Differentiable Search of Robust Neural Architectures

no code implementations CVPR 2021 Ramtin Hosseini, Xingyi Yang, Pengtao Xie

To address this problem, we propose methods to perform differentiable search of robust neural architectures.

XRayGAN: Consistency-preserving Generation of X-ray Images from Radiology Reports

no code implementations17 Jun 2020 Xingyi Yang, Nandiraju Gireesh, Eric Xing, Pengtao Xie

To address this problem, we develop methods to generate view-consistent, high-fidelity, and high-resolution X-ray images from radiology reports to facilitate radiology training of medical students.

COVID-CT-Dataset: A CT Scan Dataset about COVID-19

17 code implementations30 Mar 2020 Xingyi Yang, Xuehai He, Jinyu Zhao, Yichen Zhang, Shanghang Zhang, Pengtao Xie

Using this dataset, we develop diagnosis methods based on multi-task learning and self-supervised learning, that achieve an F1 of 0. 90, an AUC of 0. 98, and an accuracy of 0. 89.

Computed Tomography (CT) COVID-19 Diagnosis +2

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