1 citations · 2 across the 21 of their papers we have counts for
28 papers
Test-Time Training as Residual Memory for Robot Policies
Haoxuan Wang, Gengyu Zhang, Ramana Rao Kompella +2
Memory is essential for long-horizon robotic manipulation, where successful actions may depend on past events that are no longer recoverable from the current observation. As episod…
Looking Back to Move Forward: Temporal Verification for Generative Robot Policies
Haoxuan Wang, Wayne Wu, Yan Yan +1
Generative policies have emerged as a promising paradigm for robot learning, combining expressive generative action modeling with scalable imitation learning from large demonstrati…
Cue the Flow: Steering Flow-Matching Policies for Open-World Delivery Manipulation
Haoxuan Wang, Griffin Galimi, Junhua Huang +4
Open-world goods delivery requires mobile manipulators to follow free-form user instructions and manipulate potentially novel objects. Existing dual-system approaches use high-leve…
Inference of Online Newton Methods with Nesterov's Accelerated Sketching
Haoxuan Wang, Xinchen Du, Sen Na
Reliable decision-making with streaming data requires principled uncertainty quantification of online methods. While first-order methods enable efficient iterate updates, their inf…
VLA Knows Its Limits: Adaptive Execution Horizons for Robot Policies
Haoxuan Wang, Gengyu Zhang, Yan Yan +2
Action chunking has recently emerged as a standard practice in flow-based Vision-Language-Action (VLA) models. However, the effect and choice of the execution horizon - the number…
Real-Time Robot Execution with Masked Action Chunking
Haoxuan Wang, Gengyu Zhang, Yan Yan +3
Real-time execution is essential for cyber-physical systems such as robots. These systems operate in dynamic real-world environments where even small delays can undermine responsiv…
Distill Video Datasets into Images
Zhenghao Zhao, Haoxuan Wang, Kai Wang +3
Dataset distillation aims to synthesize compact yet informative datasets that allow models trained on them to achieve performance comparable to training on the full dataset. While…
TraceFlow: Dynamic 3D Reconstruction of Specular Scenes Driven by Ray Tracing
Jiachen Tao, Junyi Wu, Haoxuan Wang +3
We present TraceFlow, a novel framework for high-fidelity rendering of dynamic specular scenes by addressing two key challenges: precise reflection direction estimation and physica…
From Particles to Fields: Reframing Photon Mapping with Continuous Gaussian Photon Fields
Jiachen Tao, Benjamin Planche, Van Nguyen Nguyen +13
Accurately modeling light transport is essential for realistic image synthesis. Photon mapping provides physically grounded estimates of complex global illumination effects such as…
Motion Marionette: Rethinking Rigid Motion Transfer via Prior Guidance
Haoxuan Wang, Jiachen Tao, Junyi Wu +3
We present Motion Marionette, a zero-shot framework for rigid motion transfer from monocular source videos to single-view target images. Previous works typically employ geometric,…
Orientation-anchored Hyper-Gaussian for 4D Reconstruction from Casual Videos
Junyi Wu, Jiachen Tao, Haoxuan Wang +3
We present Orientation-anchored Gaussian Splatting (OriGS), a novel framework for high-quality 4D reconstruction from casually captured monocular videos. While recent advances exte…
Efficient Multimodal Dataset Distillation via Generative Models
Zhenghao Zhao, Haoxuan Wang, Junyi Wu +3
Dataset distillation aims to synthesize a small dataset from a large dataset, enabling the model trained on it to perform well on the original dataset. With the blooming of large l…
-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting
Zhimin Liao, Ping Wei, Ruijie Zhang +3
Forecasting the evolution of 3D scenes and generating unseen scenarios via occupancy-based world models offers substantial potential for addressing corner cases in autonomous drivi…
CaO: Rectifying Inconsistencies in Diffusion-Based Dataset Distillation
Haoxuan Wang, Zhenghao Zhao, Junyi Wu +3
The recent introduction of diffusion models in dataset distillation has shown promising potential in creating compact surrogate datasets for large, high-resolution target datasets,…
STCOcc: Sparse Spatial-Temporal Cascade Renovation for 3D Occupancy and Scene Flow Prediction
Zhimin Liao, Ping Wei, Shuaijia Chen +2
3D occupancy and scene flow offer a detailed and dynamic representation of 3D scene. Recognizing the sparsity and complexity of 3D space, previous vision-centric methods have emplo…
X-Field: A Physically Grounded Representation for 3D X-ray Reconstruction
Feiran Wang, Jiachen Tao, Junyi Wu +5
X-ray imaging is indispensable in medical diagnostics, yet its use is tightly regulated due to potential health risks. To mitigate radiation exposure, recent research focuses on ge…
UniCombine: Unified Multi-Conditional Combination with Diffusion Transformer
Haoxuan Wang, Jinlong Peng, Qingdong He +9
With the rapid development of diffusion models in image generation, the demand for more powerful and flexible controllable frameworks is increasing. Although existing methods can g…
PixelPonder: Dynamic Patch Adaptation for Enhanced Multi-Conditional Text-to-Image Generation
Yanjie Pan, Qingdong He, Zhengkai Jiang +9
Recent advances in diffusion-based text-to-image generation have demonstrated promising results through visual condition control. However, existing ControlNet-like methods struggle…
Mamba-YOLO-World: Marrying YOLO-World with Mamba for Open-Vocabulary Detection
Haoxuan Wang, Qingdong He, Jinlong Peng +3
Open-vocabulary detection (OVD) aims to detect objects beyond a predefined set of categories. As a pioneering model incorporating the YOLO series into OVD, YOLO-World is well-suite…
Distilling Long-tailed Datasets
Zhenghao Zhao, Haoxuan Wang, Yuzhang Shang +2
Dataset distillation aims to synthesize a small, information-rich dataset from a large one for efficient model training. However, existing dataset distillation methods struggle wit…
Dual-Interrelated Diffusion Model for Few-Shot Anomaly Image Generation
Ying Jin, Jinlong Peng, Qingdong He +8
The performance of anomaly inspection in industrial manufacturing is constrained by the scarcity of anomaly data. To overcome this challenge, researchers have started employing ano…
Bayesian modeling of multi-species labeling errors in ecological studies
Haoxuan Wang, Patrik Lauha, David B. Dunson
Ecological and conservation studies monitoring bird communities typically rely on species classification based on bird vocalizations. Historically, this has been based on expert vo…
PTQ4DiT: Post-training Quantization for Diffusion Transformers
Junyi Wu, Haoxuan Wang, Yuzhang Shang +2
The recent introduction of Diffusion Transformers (DiTs) has demonstrated exceptional capabilities in image generation by using a different backbone architecture, departing from tr…
Seed Optimization with Frozen Generator for Superior Zero-shot Low-light Enhancement
Yuxuan Gu, Yi Jin, Ben Wang +6
In this work, we observe that the generators, which are pre-trained on massive natural images, inherently hold the promising potential for superior low-light image enhancement agai…