10 papers
XPolicyLab: A Unified Standard and Open Ecosystem for Robot Policy Evaluation and Deployment
XPolicyLab Community, Tianxing Chen, Yue Chen +67
Robot policy evaluation and deployment remain fragmented by model-specific software dependencies, data representations, and runtime interfaces, so that connecting N policies to M e…
AlignDrive: Aligned Lateral-Longitudinal Planning for End-to-End Autonomous Driving
Yanhao Wu, Haoyang Zhang, Fei He +6
Practical autonomous driving requires models that generalize by reasoning through spatial-temporal possibilities to exclude unsafe outcomes. While state-of-the-art (SOTA) methods u…
EfficientFlow: Efficient Equivariant Flow Policy Learning for Embodied AI
Jianlei Chang, Ruofeng Mei, Wei Ke +1
Generative modeling has recently shown remarkable promise for visuomotor policy learning, enabling flexible and expressive control across diverse embodied AI tasks. However, existi…
Control Your Robot: A Unified System for Robot Control and Policy Deployment
Tian Nian, Weijie Ke, Shaolong Zhu +1
Cross-platform robot control remains difficult because hardware interfaces, data formats, and control paradigms vary widely, which fragments toolchains and slows deployment. To add…
Refining CLIP's Spatial Awareness: A Visual-Centric Perspective
Congpei Qiu, Yanhao Wu, Wei Ke +2
Contrastive Language-Image Pre-training (CLIP) excels in global alignment with language but exhibits limited sensitivity to spatial information, leading to strong performance in ze…
Generating Multimodal Driving Scenes via Next-Scene Prediction
Yanhao Wu, Haoyang Zhang, Tianwei Lin +6
Generative models in Autonomous Driving (AD) enable diverse scene creation, yet existing methods fall short by only capturing a limited range of modalities, restricting the capabil…
Monte Carlo Diffusion for Generalizable Learning-Based RANSAC
Jiale Wang, Chen Zhao, Wei Ke +1
Random Sample Consensus (RANSAC) is a fundamental approach for robustly estimating parametric models from noisy data. Existing learning-based RANSAC methods utilize deep learning t…
Coherent and Multi-modality Image Inpainting via Latent Space Optimization
Lingzhi Pan, Tong Zhang, Bingyuan Chen +4
With the advancements in denoising diffusion probabilistic models (DDPMs), image inpainting has significantly evolved from merely filling information based on nearby regions to gen…
Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object Exchange
Yanhao Wu, Tong Zhang, Wei Ke +3
In the realm of point cloud scene understanding, particularly in indoor scenes, objects are arranged following human habits, resulting in objects of certain semantics being closely…
Language-Driven Visual Consensus for Zero-Shot Semantic Segmentation
Zicheng Zhang, Tong Zhang, Yi Zhu +4
The pre-trained vision-language model, exemplified by CLIP, advances zero-shot semantic segmentation by aligning visual features with class embeddings through a transformer decoder…