6 citations · 16 across the 31 of their papers we have counts for
15 papers · 1 filter
SpikeOcc: Towards Resilient Multimodal 3D Occupancy Perception via Spiking Experts
Yiding Sun, Zijie Xu, Hongqiang Lin +7
Multimodal 3D occupancy prediction underpins safe autonomous driving through comprehensive scene understanding. However, existing methods have largely pursued higher accuracy throu…
Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models
Xin Wang, Wenxuan Liu, Tongtong Feng +1
Large-scale video generation models are increasingly described as world models because they can learn rich spatiotemporal regularities from visual data. However, we argue that an i…
Yuvion VL: A Multimodal Foundation Model for Adversarial Content and AI Safety
Shikai Qiu, Xiaowen Xu, Benlei Cui +55
General-purpose models often struggle to reliably identify and understand real-world multimodal risks, largely due to the inherent multimodal adversarial nature of content and AI s…
Brain-Inspired Multimodal Spiking Neural Network for Image-Text Retrieval
Xintao Zong, Xian Zhong, Wenxuan Liu +3
Spiking neural networks (SNNs) have recently shown strong potential in unimodal visual and textual tasks, yet building a directly trained, low-energy, and high-performance SNN for…
Scone: Bridging Composition and Distinction in Subject-Driven Image Generation via Unified Understanding-Generation Modeling
Yuran Wang, Bohan Zeng, Chengzhuo Tong +6
Subject-driven image generation has advanced from single- to multi-subject composition, while neglecting distinction, the ability to distinguish and generate the correct subject wh…
SPAN: Continuous Modeling of Suspicion Progression for Temporal Intention Localization
Xinyi Hu, Yuran Wang, Ruixu Zhang +3
Temporal Intention Localization (TIL) is crucial for video surveillance, focusing on identifying varying levels of suspicious intentions to improve security monitoring. However, ex…
HAD: Hierarchical Asymmetric Distillation to Bridge Spatio-Temporal Gaps in Event-Based Object Tracking
Yao Deng, Xian Zhong, Wenxuan Liu +3
RGB cameras excel at capturing rich texture details with high spatial resolution, whereas event cameras offer exceptional temporal resolution and a high dynamic range (HDR). Levera…
Beyond the Individual: Introducing Group Intention Forecasting with SHOT Dataset
Ruixu Zhang, Yuran Wang, Xinyi Hu +5
Intention recognition has traditionally focused on individual intentions, overlooking the complexities of collective intentions in group settings. To address this limitation, we in…
SOTA: Spike-Navigated Optimal TrAnsport Saliency Region Detection in Composite-bias Videos
Wenxuan Liu, Yao Deng, Kang Chen +3
Existing saliency detection methods struggle in real-world scenarios due to motion blur and occlusions. In contrast, spike cameras, with their high temporal resolution, significant…
Foveated Instance Segmentation
Hongyi Zeng, Wenxuan Liu, Tianhua Xia +3
Instance segmentation is essential for augmented reality and virtual reality (AR/VR) as it enables precise object recognition and interaction, enhancing the integration of virtual…
SpikeDerain: Unveiling Clear Videos from Rainy Sequences Using Color Spike Streams
Hanwen Liang, Xian Zhong, Wenxuan Liu +4
Restoring clear frames from rainy videos presents a significant challenge due to the rapid motion of rain streaks. Traditional frame-based visual sensors, which capture scene conte…
Differential Coding for Training-Free ANN-to-SNN Conversion
Zihan Huang, Wei Fang, Tong Bu +6
Spiking Neural Networks (SNNs) exhibit significant potential due to their low energy consumption. Converting Artificial Neural Networks (ANNs) to SNNs is an efficient way to achiev…
FovealNet: Advancing AI-Driven Gaze Tracking Solutions for Optimized Foveated Rendering System Performance in Virtual Reality
Wenxuan Liu, Monde Duinkharjav, Qi Sun +1
Leveraging real-time eye-tracking, foveated rendering optimizes hardware efficiency and enhances visual quality virtual reality (VR). This approach leverages eye-tracking technique…
HQ-DiT: Efficient Diffusion Transformer with FP4 Hybrid Quantization
Wenxuan Liu, Sai Qian Zhang
Diffusion Transformers (DiTs) have recently gained substantial attention in both industrial and academic fields for their superior visual generation capabilities, outperforming tra…
End-to-End Video Object Detection with Spatial-Temporal Transformers
Lu He, Qianyu Zhou, Xiangtai Li +7
Recently, DETR and Deformable DETR have been proposed to eliminate the need for many hand-designed components in object detection while demonstrating good performance as previous c…