28 citations · 37 across the 14 of their papers we have counts for
14 papers
Wonder: Video World Model Done Better
Jiacong Xu, Hanwen Jiang, Zhixin Shu +3
We present Wonder, a general-purpose video world model for real-time, camera-controllable world exploration. Given an image or a conditional video, Wonder constructs a playable wor…
InstantHDR: Single-forward Gaussian Splatting Initialization for HDR 3D Reconstruction
Dingqiang Ye, Jiacong Xu, Jianglu Ping +3
High dynamic range (HDR) novel view synthesis (NVS) aims to reconstruct HDR scenes from multi-exposure low dynamic range (LDR) images. Existing HDR pipelines heavily rely on known…
Endless World: Real-Time 3D-Aware Long Video Generation
Ke Zhang, Yiqun Mei, Jiacong Xu +1
Producing long, coherent video sequences with stable 3D structure remains a major challenge, particularly in streaming scenarios. Motivated by this, we introduce Endless World, a r…
FreeViS: Training-free Video Stylization with Inconsistent References
Jiacong Xu, Yiqun Mei, Ke Zhang +1
Video stylization plays a key role in content creation, but it remains a challenging problem. Naïvely applying image stylization frame-by-frame hurts temporal consistency and reduc…
Think Before You Diffuse: Infusing Physical Rules into Video Diffusion
Ke Zhang, Cihan Xiao, Jiacong Xu +2
Recent video diffusion models have demonstrated their great capability in generating visually-pleasing results, while synthesizing the correct physical effects in generated videos…
Filter Images First, Generate Instructions Later: Pre-Instruction Data Selection for Visual Instruction Tuning
Bardia Safaei, Faizan Siddiqui, Jiacong Xu +2
Visual instruction tuning (VIT) for large vision-language models (LVLMs) requires training on expansive datasets of image-instruction pairs, which can be costly. Recent efforts in…
Towards Zero-Shot Anomaly Detection and Reasoning with Multimodal Large Language Models
Jiacong Xu, Shao-Yuan Lo, Bardia Safaei +2
Zero-Shot Anomaly Detection (ZSAD) is an emerging AD paradigm. Unlike the traditional unsupervised AD setting that requires a large number of normal samples to train a model, ZSAD…
XYScanNet: A State Space Model for Single Image Deblurring
Hanzhou Liu, Chengkai Liu, Jiacong Xu +2
Deep state-space models (SSMs), like recent Mamba architectures, are emerging as a promising alternative to CNN and Transformer networks. Existing Mamba-based restoration methods p…
Reference-based Controllable Scene Stylization with Gaussian Splatting
Yiqun Mei, Jiacong Xu, Vishal M. Patel
Referenced-based scene stylization that edits the appearance based on a content-aligned reference image is an emerging research area. Starting with a pretrained neural radiance fie…
Wild-GS: Real-Time Novel View Synthesis from Unconstrained Photo Collections
Jiacong Xu, Yiqun Mei, Vishal M. Patel
Photographs captured in unstructured tourist environments frequently exhibit variable appearances and transient occlusions, challenging accurate scene reconstruction and inducing a…
Leveraging Thermal Modality to Enhance Reconstruction in Low-Light Conditions
Jiacong Xu, Mingqian Liao, K Ram Prabhakar +1
Neural Radiance Fields (NeRF) accomplishes photo-realistic novel view synthesis by learning the implicit volumetric representation of a scene from multi-view images, which faithful…
Communication-Efficient Design of Learning System for Energy Demand Forecasting of Electrical Vehicles
Jiacong Xu, Riley Kilfoyle, Zixiang Xiong +1
Machine learning (ML) applications to time series energy utilization forecasting problems are a challenging assignment due to a variety of factors. Chief among these is the non-hom…
Animal3D: A Comprehensive Dataset of 3D Animal Pose and Shape
Jiacong Xu, Yi Zhang, Jiawei Peng +17
Accurately estimating the 3D pose and shape is an essential step towards understanding animal behavior, and can potentially benefit many downstream applications, such as wildlife c…
PIDNet: A Real-time Semantic Segmentation Network Inspired by PID Controllers
Jiacong Xu, Zixiang Xiong, Shankar P. Bhattacharyya
Two-branch network architecture has shown its efficiency and effectiveness in real-time semantic segmentation tasks. However, direct fusion of high-resolution details and low-frequ…