Yu-Xiong Wang
Assistant Professor
Studies computer vision and machine learning, including open-world perception, few-shot learning and 3D and video generation.
Yu-Xiong Wang's lab at UIUC works on 3D vision & neural rendering, video understanding and robot perception & SLAM. 56 papers since 2023, 50 at top venues, mostly CVPR and NeurIPS. 13 PhD students. Applications close .
At a glance
- papers, 2023–2026
- 15/ year
- at T1 venues
- 89%
- PhD students
- 13
- MS students
- 0
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 11 papers2025 · T1 11
- 20 papers2024 · T1 19
- 25 papers2023 · T1 20
T1 venuesOtherVenues: CVPR, NeurIPS, ICLR, ICCV, ICML
Research focuspaper titles that use each topic's words
- 3D vision & neural rendering8 papers
- Video understanding4 papers
- Robot perception & SLAM4 papers
- open-world1 paper
- few-shot learning0 papers
Paper list
From the lab homepage.
202511 papers
- ICLR (T1)3DGS-Drag: Dragging Gaussians for Intuitive Point-Based 3D Editing
- ICLR (T1)Aligning Generative Denoising with Discriminative Objectives Unleashes Diffusion for Visual Perception
- CVPR (T1)Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought
- ICLR (T1)Diff-2-in-1: Bridging Generation and Dense Perception with Diffusion Models
- CVPR (T1)Floating No More: Object-Ground Reconstruction from a Single Image
- CVPR (T1)GLUS: Global-Local Reasoning Unified into A Single Large Language Model for Video Segmentation
- CVPR (T1)InterAct: Advancing Large-Scale Versatile 3D Human-Object Interaction Generation
- CVPR (T1)InterMimic: Towards Universal Whole-Body Control for Physics-Based Human-Object Interactions
- CVPR (T1)RandAR: Decoder-only Autoregressive Visual Generation in Random Orders
- ICLR (T1)RTDiff: Reverse Trajectory Synthesis via Diffusion for Offline Reinforcement Learning
- ICLR (T1)Swiss Army Knife: Synergizing Biases in Knowledge from Vision Foundation Models for Multi-Task Learning
202420 papers
- ECCV (T1)AlignDiff: Aligning Diffusion Models for General Few-Shot Segmentation
- Findings of ACLAligning Large Multimodal Models with Factually Augmented RLHF
- ICML (T1)ATraDiff: Accelerating Online Reinforcement Learning with Imaginary Trajectories
- CVPR (T1)ConsistDreamer: 3D-Consistent 2D Diffusion for High-Fidelity Scene Editing
- ICLR (T1)Frozen Transformers in Language Models Are Effective Visual Encoder Layers
- CVPR (T1)Instruct 4D-to-4D: Editing 4D Scenes as Pseudo-3D Scenes Using 2D Diffusion
- NeurIPS (T1)InstructG2I: Synthesizing Images from Multimodal Attributed Graphs
- NeurIPS (T1)InterDreamer: Zero-Shot Text to 3D Dynamic Human-Object Interaction
- ICML (T1)Language Agent Tree Search Unifies Reasoning, Acting, and Planning in Language Models
- NeurIPS (T1)Lexicon3D: Probing Visual Foundation Models for Complex 3D Scene Reasoning
- ICML (T1)Offline Imitation from Observation via Primal Wasserstein State Occupancy Matching
- NeurIPS (T1)ProEdit: Simple Progression is All You Need for High-Quality 3D Scene Editing
202325 papers
- NeurIPS (T1)A Simple Solution for Offline Imitation from Observations and Examples with Possibly Incomplete Trajectories
- CVPR (T1)BEV-Guided Multi-Modality Fusion for Driving Perception
- WACVBeyond RGB: Scene-Property Synthesis with Neural Radiance Fields
- ICCV (T1)Contrastive Learning Relies More on Spatial Inductive Bias Than Supervised Learning: An Empirical Study
- CVPR (T1)Contrastive Mean Teacher for Domain Adaptive Object Detectors
- NeurIPS (T1)Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models
- WACVDo Pre-Trained Models Benefit Equally in Continual Learning?
- IROS (T1)DualCross: Cross-Modality Cross-Domain Adaptation for Monocular BEV Perception
- CVPR WorkshopFrom N to N+1: Learning to Detect Novel Animals with SAM in the Wild
- CVPR WorkshopGAPS: Few-Shot Incremental Semantic Segmentation via Guided Copy-Paste Synthesis
- NeurIPS (T1)HASSOD: Hierarchical Adaptive Self-Supervised Object Detection
- ICCV (T1)Improving Equivariance in State-of-the-Art Supervised Depth and Normal Predictors
Where alumni went
Alumni are not listed on the lab homepage.
Apply to UIUCFall 2027
UIUC Siebel Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- optional
- English
- TOEFL iBT / IELTS
- Fee
- USD 90
Not yet confirmed for this intake.
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Data
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- Collected
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