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20232026
most citedSparse Diffusion Policy: A Sparse, Reusable, and Flexible Policy for Robot Learning

1 citations · 2 across the 19 of their papers we have counts for

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12 papers · 1 filter

cs.CV2026

LaMo: Self-Supervised Latent Motion Priors for Physical Realism in Video Generation

Bo Jiang, Depu Meng, Yihan Hu +3

Modern video generators produce visually compelling clips but still struggle with physical and motion consistency, limiting their use as reliable world simulators. Existing remedie…

cs.CV2026

Teaching Video Generators to Remember: Eliciting Dynamic Memory for Out-of-Sight State Evolution

Tianshuo Xu, Yichen Xie, Depu Meng +5

Video world models should maintain evolving states when evidence is unobserved, yet current generators often freeze hidden states upon interruption. This is not simply a capacity p…

cs.CV2026

EndoVGGT: GNN-Enhanced Depth Estimation for Surgical 3D Reconstruction

Falong Fan, Yi Xie, Arnis Lektauers +2

Accurate 3D reconstruction of deformable soft tissues is essential for surgical robotic perception. However, low-texture surfaces, specular highlights, and instrument occlusions of…

cs.CV2026

UniQueR: Unified Query-based Feedforward 3D Reconstruction

Chensheng Peng, Quentin Herau, Jiezhi Yang +6

We present UniQueR, a unified query-based feedforward framework for efficient and accurate 3D reconstruction from unposed images. Existing feedforward models such as DUSt3R, VGGT,…

cs.CV2026

RAYNOVA: Scale-Temporal Autoregressive World Modeling in Ray Space

Yichen Xie, Chensheng Peng, Mazen Abdelfattah +6

World foundation models aim to simulate the evolution of the real world with physically plausible behavior. Unlike prior methods that handle spatial and temporal correlations separ…

cs.CV2024

X-Drive: Cross-modality consistent multi-sensor data synthesis for driving scenarios

Yichen Xie, Chenfeng Xu, Chensheng Peng +6

Recent advancements have exploited diffusion models for the synthesis of either LiDAR point clouds or camera image data in driving scenarios. Despite their success in modeling sing…

cs.CV2024

DeSiRe-GS: 4D Street Gaussians for Static-Dynamic Decomposition and Surface Reconstruction for Urban Driving Scenes

Chensheng Peng, Chengwei Zhang, Yixiao Wang +6

We present DeSiRe-GS, a self-supervised gaussian splatting representation, enabling effective static-dynamic decomposition and high-fidelity surface reconstruction in complex drivi…

cs.CV2024

TrajSSL: Trajectory-Enhanced Semi-Supervised 3D Object Detection

Philip Jacobson, Yichen Xie, Mingyu Ding +4

Semi-supervised 3D object detection is a common strategy employed to circumvent the challenge of manually labeling large-scale autonomous driving perception datasets. Pseudo-labeli…

cs.CV2024

Optimizing Diffusion Models for Joint Trajectory Prediction and Controllable Generation

Yixiao Wang, Chen Tang, Lingfeng Sun +8

Diffusion models are promising for joint trajectory prediction and controllable generation in autonomous driving, but they face challenges of inefficient inference steps and high c…

cs.CV2024

RoadBEV: Road Surface Reconstruction in Bird's Eye View

Tong Zhao, Lei Yang, Yichen Xie +3

Road surface conditions, especially geometry profiles, enormously affect driving performance of autonomous vehicles. Vision-based online road reconstruction promisingly captures ro…

cs.CV2024

Cohere3D: Exploiting Temporal Coherence for Unsupervised Representation Learning of Vision-based Autonomous Driving

Yichen Xie, Hongge Chen, Gregory P. Meyer +6

Due to the lack of depth cues in images, multi-frame inputs are important for the success of vision-based perception, prediction, and planning in autonomous driving. Observations f…

cs.CV2023★ 1 cited

Towards Free Data Selection with General-Purpose Models

Yichen Xie, Mingyu Ding, Masayoshi Tomizuka +1

A desirable data selection algorithm can efficiently choose the most informative samples to maximize the utility of limited annotation budgets. However, current approaches, represe…