24 citations · 27 across the 8 of their papers we have counts for
10 papers
Region-Level Policy Optimization for Fine-grained MLLM Perception
Yuheng Shi, Xiaohuan Pei, Minjing Dong +1
Fine-grained visual perception in MLLMs is commonly improved by raising the resolution, but the added visual tokens inflate vision-encoding and language-model prefilling costs. We…
Q-Zoom: Query-Aware Adaptive Perception for Efficient Multimodal Large Language Models
Yuheng Shi, Xiaohuan Pei, Linfeng Wen +2
MLLMs require high-resolution visual inputs for fine-grained tasks like document understanding and dense scene perception. However, current global resolution scaling paradigms indi…
Action-aware Dynamic Pruning for Efficient Vision-Language-Action Manipulation
Xiaohuan Pei, Yuxing Chen, Siyu Xu +3
Robotic manipulation with Vision-Language-Action models requires efficient inference over long-horizon multi-modal context, where attention to dense visual tokens dominates computa…
Catching the Details: Self-Distilled RoI Predictors for Fine-Grained MLLM Perception
Yuheng Shi, Xiaohuan Pei, Minjing Dong +1
Multimodal Large Language Models (MLLMs) require high-resolution visual information to perform fine-grained perception, yet processing entire high-resolution images is computationa…
Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation
Yuheng Shi, Minjing Dong, Chang Xu
While Contrastive Language-Image Pre-training (CLIP) has advanced open-vocabulary predictions, its performance on semantic segmentation remains suboptimal. This shortfall primarily…
VSSD: Vision Mamba with Non-Causal State Space Duality
Yuheng Shi, Minjing Dong, Mingjia Li +1
Vision transformers have significantly advanced the field of computer vision, offering robust modeling capabilities and global receptive field. However, their high computational de…
Practical Video Object Detection via Feature Selection and Aggregation
Yuheng Shi, Tong Zhang, Xiaojie Guo
Compared with still image object detection, video object detection (VOD) needs to particularly concern the high across-frame variation in object appearance, and the diverse deterio…
Multi-Scale VMamba: Hierarchy in Hierarchy Visual State Space Model
Yuheng Shi, Minjing Dong, Chang Xu
Despite the significant achievements of Vision Transformers (ViTs) in various vision tasks, they are constrained by the quadratic complexity. Recently, State Space Models (SSMs) ha…
TSTTC: A Large-Scale Dataset for Time-to-Contact Estimation in Driving Scenarios
Yuheng Shi, Zehao Huang, Yan Yan +2
Time-to-Contact (TTC) estimation is a critical task for assessing collision risk and is widely used in various driver assistance and autonomous driving systems. The past few decade…
YOLOV: Making Still Image Object Detectors Great at Video Object Detection
Yuheng Shi, Naiyan Wang, Xiaojie Guo
Video object detection (VID) is challenging because of the high variation of object appearance as well as the diverse deterioration in some frames. On the positive side, the detect…