9 papers
One RL to See Them All: Visual Triple Unified Reinforcement Learning
Yan Ma, Linge Du, Xuyang Shen +7
Reinforcement learning (RL) is becoming an important direction for post-training vision-language models (VLMs), but public training methodologies for unified multimodal RL remain m…
SSR: A Training-Free Approach for Streaming 3D Reconstruction
Hui Deng, Yuxin Mao, Yuxin He +1
Streaming 3D reconstruction demands long-horizon state updates under strict latency constraints, yet stateful recurrent models often suffer from geometric drift as errors accumulat…
SABER: Spatially Consistent 3D Universal Adversarial Objects for BEV Detectors
Aixuan Li, Mochu Xiang, Bosen Hou +3
Adversarial robustness of BEV 3D object detectors is critical for autonomous driving (AD). Existing invasive attacks require altering the target vehicle itself (e.g. attaching patc…
RnG: A Unified Transformer for Complete 3D Modeling from Partial Observations
Mochu Xiang, Zhelun Shen, Xuesong Li +7
Human perceive the 3D world through 2D observations from limited viewpoints. While recent feed-forward generalizable 3D reconstruction models excel at recovering 3D structures from…
Learning Spatial Decay for Vision Transformers
Yuxin Mao, Zhen Qin, Jinxing Zhou +4
Vision Transformers (ViTs) have revolutionized computer vision, yet their self-attention mechanism lacks explicit spatial inductive biases, leading to suboptimal performance on spa…
Autoregressive Image Generation with Linear Complexity: A Spatial-Aware Decay Perspective
Yuxin Mao, Zhen Qin, Jinxing Zhou +6
Autoregressive (AR) models have garnered significant attention in image generation for their ability to effectively capture both local and global structures within visual data. How…