32 citations · 55 across the 17 of their papers we have counts for
20 papers
Annotations as Rollouts: Efficient and Scalable Reinforcement Learning for Video MLLMs
Yunheng Li, Guohong Mu, Hao Li +4
Multimodal large language models (MLLMs) have become a prevailing paradigm for unified video perception. However, post-training on large multi-task datasets remains challenging, as…
P2Fusion: Prompt-based Progressive Infrared-Visible Image Fusion via Dual-Prior Distillation
Yi Shi, Huichao Xie, Yuqing Wang +7
Infrared-visible image fusion (IVIF) is pivotal for multimodal perception, yet reconciling the inherent information disparity between thermal and textural features remains a fundam…
UniRef-UAV: A Multimodal Benchmark for Universal Referring in UAV Imagery
Haibin Tian, Huichao Xie, Xuelin Qian +3
Unmanned aerial vehicles (UAVs) increasingly rely on visual grounding capabilities to localize task-relevant targets from diverse instructions in complex aerial scenes. Existing re…
Saliency-R1: Incentivizing Unified Saliency Reasoning Capability in MLLM with Confidence-Guided Reinforcement Learning
Long Li, Shuichen Ji, Ziyang Luo +4
Although multimodal large language models (MLLMs) excel in high-level vision-language reasoning, they lack inherent awareness of visual saliency, making it difficult to identify ke…
IrisNet: Infrared Image Status Awareness Meta Decoder for Infrared Small Targets Detection
Xuelin Qian, Jiaming Lu, Zixuan Wang +4
Infrared Small Target Detection (IRSTD) faces significant challenges due to low signal-to-noise ratios, complex backgrounds, and the absence of discernible target features. While d…
Dual-Granularity Semantic Prompting for Language Guidance Infrared Small Target Detection
Zixuan Wang, Haoran Sun, Jiaming Lu +5
Infrared small target detection remains challenging due to limited feature representation and severe background interference, resulting in sub-optimal performance. While recent CLI…
Hierarchical Mixing Architecture for Low-light RAW Image Enhancement
Xianmin Chen, Peiliang Huang, Longfei Han +2
With the rapid development of deep learning, low-light RAW image enhancement (LLRIE) has achieved remarkable progress. However, the challenge that how to simultaneously achieve str…
STRIDER: Navigation via Instruction-Aligned Structural Decision Space Optimization
Diqi He, Xuehao Gao, Hao Li +2
The Zero-shot Vision-and-Language Navigation in Continuous Environments (VLN-CE) task requires agents to navigate previously unseen 3D environments using natural language instructi…
Pursuing Temporal-Consistent Video Virtual Try-On via Dynamic Pose Interaction
Dong Li, Wenqi Zhong, Wei Yu +5
Video virtual try-on aims to seamlessly dress a subject in a video with a specific garment. The primary challenge involves preserving the visual authenticity of the garment while d…
Seamless Detection: Unifying Salient Object Detection and Camouflaged Object Detection
Yi Liu, Chengxin Li, Xiaohui Dong +4
Achieving joint learning of Salient Object Detection (SOD) and Camouflaged Object Detection (COD) is extremely challenging due to their distinct object characteristics, i.e., salie…
LangSurf: Language-Embedded Surface Gaussians for 3D Scene Understanding
Hao Li, Minghan Qin, Zhengyu Zou +6
Applying Gaussian Splatting to perception tasks for 3D scene understanding is becoming increasingly popular. Most existing works primarily focus on rendering 2D feature maps from n…
PolSAM: Polarimetric Scattering Mechanism Informed Segment Anything Model
Yuqing Wang, Zhongling Huang, Shuxin Yang +4
PolSAR data presents unique challenges due to its rich and complex characteristics. Existing data representations, such as complex-valued data, polarimetric features, and amplitude…
CONDA: Condensed Deep Association Learning for Co-Salient Object Detection
Long Li, Nian Liu, Dingwen Zhang +6
Inter-image association modeling is crucial for co-salient object detection. Despite satisfactory performance, previous methods still have limitations on sufficient inter-image ass…
Mamba Capsule Routing Towards Part-Whole Relational Camouflaged Object Detection
Dingwen Zhang, Liangbo Cheng, Yi Liu +2
The part-whole relational property endowed by Capsule Networks (CapsNets) has been known successful for camouflaged object detection due to its segmentation integrity. However, the…
Retinex-RAWMamba: Bridging Demosaicing and Denoising for Low-Light RAW Image Enhancement
Xianmin Chen, Longfei Han, Peiliang Huang +3
Low-light image enhancement, particularly in cross-domain tasks such as mapping from the raw domain to the sRGB domain, remains a significant challenge. Many deep learning-based me…
ASPS: Augmented Segment Anything Model for Polyp Segmentation
Huiqian Li, Dingwen Zhang, Jieru Yao +3
Polyp segmentation plays a pivotal role in colorectal cancer diagnosis. Recently, the emergence of the Segment Anything Model (SAM) has introduced unprecedented potential for polyp…
Center-Sensitive Kernel Optimization for Efficient On-Device Incremental Learning
Dingwen Zhang, Yan Li, De Cheng +2
To facilitate the evolution of edge intelligence in ever-changing environments, we study on-device incremental learning constrained in limited computation resource in this paper. C…
Boosting Medical Image-based Cancer Detection via Text-guided Supervision from Reports
Guangyu Guo, Jiawen Yao, Yingda Xia +7
The absence of adequately sufficient expert-level tumor annotations hinders the effectiveness of supervised learning based opportunistic cancer screening on medical imaging. Clinic…
Unsupervised Pre-training with Language-Vision Prompts for Low-Data Instance Segmentation
Dingwen Zhang, Hao Li, Diqi He +4
In recent times, following the paradigm of DETR (DEtection TRansformer), query-based end-to-end instance segmentation (QEIS) methods have exhibited superior performance compared to…
Revisiting the Power of Prompt for Visual Tuning
Yuzhu Wang, Lechao Cheng, Chaowei Fang +3
Visual prompt tuning (VPT) is a promising solution incorporating learnable prompt tokens to customize pre-trained models for downstream tasks. However, VPT and its variants often e…