1 citations · 1 across the 19 of their papers we have counts for
23 papers
-PnP: Plug-and-Play Denoising for Scientific Imaging with Self-Supervised Score Priors
Yukun Cui, Jiangshe Zhang, Shuang Xu +6
Modern image restoration methods increasingly rely on large-scale supervised training, yet clean targets are often prohibitively difficult to obtain in scientific imaging modalitie…
Coefficientwise Extremality and Rigidity for Independent Sets in Bipartite Graph Covers
Yusuke Watanabe
Let be a finite bipartite graph and let be an -fold cover. We compare independent sets of with those of the trivial cover, consisting of di…
Teaching Foundation Models to Read mmWave: Pose-Guided Kinematic Representation for Human Behavior Understanding
Duo Zhang, Zhehui Yin, Zhiyun Yao +8
Large language model agents need to perceive human behavior in physical environments. Millimeter-wave (mmWave) radar provides a privacy-friendly and contactless sensing modality, b…
Echo-Forcing: A Scene Memory Framework for Interactive Long Video Generation
Mingqiang Wu, Weilun Feng, Zhefeng Zhang +8
Autoregressive video diffusion models enable open-ended generation through local attention and KV caching. However, existing training-free long-video optimization methods mainly fo…
Robust Spatiotemporal Motion Planning for Multi-Agent Autonomous Racing via Topological Gap Identification and Accelerated MPC
Mingyi Zhang, Cheng Hu, Yiqin Wang +3
High-speed multi-agent autonomous racing demands robust spatiotemporal planning and precise control under strict computational limits. Current methods often oversimplify interactio…
PicoSAM3: Real-Time In-Sensor Region-of-Interest Segmentation
Pietro Bonazzi, Nicola Farronato, Stefan Zihlmann +2
Real-time, on-device segmentation is critical for latency-sensitive and privacy-aware applications such as smart glasses and Internet-of-Things devices. We introduce PicoSAM3, a li…
WorldCache: Accelerating World Models for Free via Heterogeneous Token Caching
Weilun Feng, Guoxin Fan, Haotong Qin +10
Diffusion-based world models have shown strong potential for unified world simulation, but the iterative denoising remains too costly for interactive use and long-horizon rollouts.…
MambaVF: State Space Model for Efficient Video Fusion
Zixiang Zhao, Yukun Cui, Lilun Deng +4
Video fusion aims to integrate complementary information from multiple source videos while preserving temporal consistency. Effective modeling of temporal dynamics is essential to…
Quantized Visual Geometry Grounded Transformer
Weilun Feng, Haotong Qin, Mingqiang Wu +8
Learning-based 3D reconstruction models, represented by Visual Geometry Grounded Transformers (VGGTs), have made remarkable progress with the use of large-scale transformers. Their…
Post-Training Quantization for Video Matting
Tianrui Zhu, Houyuan Chen, Ruihao Gong +3
Video matting is crucial for applications such as film production and virtual reality, yet deploying its computationally intensive models on resource-constrained devices presents c…
Event-Priori-Based Vision-Language Model for Efficient Visual Understanding
Haotong Qin, Cheng Hu, Michele Magno
Large Language Model (LLM)-based Vision-Language Models (VLMs) have substantially extended the boundaries of visual understanding capabilities. However, their high computational de…
PicoSAM2: Low-Latency Segmentation In-Sensor for Edge Vision Applications
Pietro Bonazzi, Nicola Farronato, Stefan Zihlmann +2
Real-time, on-device segmentation is critical for latency-sensitive and privacy-aware applications like smart glasses and IoT devices. We introduce PicoSAM2, a lightweight (1.3M pa…
Q-SAM2: Accurate Quantization for Segment Anything Model 2
Nicola Farronato, Florian Scheidegger, Mattia Rigotti +3
The Segment Anything Model 2 (SAM2) is a powerful foundation model for promptable segmentation. However, its high computational and memory costs are a major barrier to deployment o…
Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers
Weilun Feng, Chuanguang Yang, Haotong Qin +8
Diffusion transformers (DiT) have demonstrated exceptional performance in video generation. However, their large number of parameters and high computational complexity limit their…
RGB-Event Fusion with Self-Attention for Collision Prediction
Pietro Bonazzi, Christian Vogt, Michael Jost +4
Ensuring robust and real-time obstacle avoidance is critical for the safe operation of autonomous robots in dynamic, real-world environments. This paper proposes a neural network f…
An Empirical Study of Qwen3 Quantization
Xingyu Zheng, Yuye Li, Haoran Chu +7
The Qwen series has emerged as a leading family of open-source Large Language Models (LLMs), demonstrating remarkable capabilities in natural language understanding tasks. With the…
Enhancing Autonomous Driving Systems with On-Board Deployed Large Language Models
Nicolas Baumann, Cheng Hu, Paviththiren Sivasothilingam +4
Neural Networks (NNs) trained through supervised learning struggle with managing edge-case scenarios common in real-world driving due to the intractability of exhaustive datasets c…
Q&C: When Quantization Meets Cache in Efficient Image Generation
Xin Ding, Xin Li, Haotong Qin +1
Quantization and cache mechanisms are typically applied individually for efficient Diffusion Transformers (DiTs), each demonstrating notable potential for acceleration. However, th…
Q-MambaIR: Accurate Quantized Mamba for Efficient Image Restoration
Yujie Chen, Haotong Qin, Zhang Zhang +3
State-Space Models (SSMs) have attracted considerable attention in Image Restoration (IR) due to their ability to scale linearly sequence length while effectively capturing long-di…
FSDP: Fast and Safe Data-Driven Overtaking Trajectory Planning for Head-to-Head Autonomous Racing Competitions
Cheng Hu, Jihao Huang, Wule Mao +7
Generating overtaking trajectories in autonomous racing is a challenging task, as the trajectory must satisfy the vehicle's dynamics and ensure safety and real-time performance run…
MPQ-DM: Mixed Precision Quantization for Extremely Low Bit Diffusion Models
Weilun Feng, Haotong Qin, Chuanguang Yang +7
Diffusion models have received wide attention in generation tasks. However, the expensive computation cost prevents the application of diffusion models in resource-constrained scen…
GWQ: Gradient-Aware Weight Quantization for Large Language Models
Yihua Shao, Yan Gu, Siyu Chen +12
Large language models (LLMs) show impressive performance in solving complex language tasks. However, its large number of parameters presents significant challenges for the deployme…
ODDN: Addressing Unpaired Data Challenges in Open-World Deepfake Detection on Online Social Networks
Renshuai Tao, Manyi Le, Chuangchuang Tan +3
Despite significant advances in deepfake detection, handling varying image quality, especially due to different compressions on online social networks (OSNs), remains challenging.…