11 citations · 25 across the 29 of their papers we have counts for
21 papers · 1 filter
EvoGUI: An Evolution-Aware Benchmark for GUI State-Transition Understanding
Yaohan Yang, Minglei Shi, Borui Zhang +2
GUI agents must reason about how actions transform interface states, but end-to-end success rates entangle this ability with perception, grounding, planning, and recovery. We intro…
IGL-Nav: Incremental 3D Gaussian Localization for Image-goal Navigation
Wenxuan Guo, Xiuwei Xu, Hang Yin +4
Visual navigation with an image as goal is a fundamental and challenging problem. Conventional methods either rely on end-to-end RL learning or modular-based policy with topologica…
Vision Generalist Model: A Survey
Ziyi Wang, Yongming Rao, Shuofeng Sun +8
Recently, we have witnessed the great success of the generalist model in natural language processing. The generalist model is a general framework trained with massive data and is a…
UniPre3D: Unified Pre-training of 3D Point Cloud Models with Cross-Modal Gaussian Splatting
Ziyi Wang, Yanran Zhang, Jie Zhou +1
The scale diversity of point cloud data presents significant challenges in developing unified representation learning techniques for 3D vision. Currently, there are few unified 3D…
EfficientLLaVA:Generalizable Auto-Pruning for Large Vision-language Models
Yinan Liang, Ziwei Wang, Xiuwei Xu +2
While multimodal large language models demonstrate strong performance in complex reasoning tasks, they pose significant challenges related to model complexity during deployment, es…
UniGoal: Towards Universal Zero-shot Goal-oriented Navigation
Hang Yin, Xiuwei Xu, Lingqing Zhao +3
In this paper, we propose a general framework for universal zero-shot goal-oriented navigation. Existing zero-shot methods build inference framework upon large language models (LLM…
XMask3D: Cross-modal Mask Reasoning for Open Vocabulary 3D Semantic Segmentation
Ziyi Wang, Yanbo Wang, Xumin Yu +2
Existing methodologies in open vocabulary 3D semantic segmentation primarily concentrate on establishing a unified feature space encompassing 3D, 2D, and textual modalities. Nevert…
SG-Nav: Online 3D Scene Graph Prompting for LLM-based Zero-shot Object Navigation
Hang Yin, Xiuwei Xu, Zhenyu Wu +2
In this paper, we propose a new framework for zero-shot object navigation. Existing zero-shot object navigation methods prompt LLM with the text of spatially closed objects, which…
OPONeRF: One-Point-One NeRF for Robust Neural Rendering
Yu Zheng, Yueqi Duan, Kangfu Zheng +3
In this paper, we propose a One-Point-One NeRF (OPONeRF) framework for robust scene rendering. Existing NeRFs are designed based on a key assumption that the target scene remains u…
Q-VLM: Post-training Quantization for Large Vision-Language Models
Changyuan Wang, Ziwei Wang, Xiuwei Xu +3
In this paper, we propose a post-training quantization framework of large vision-language models (LVLMs) for efficient multi-modal inference. Conventional quantization methods sequ…
FlowTurbo: Towards Real-time Flow-Based Image Generation with Velocity Refiner
Wenliang Zhao, Minglei Shi, Xumin Yu +2
Building on the success of diffusion models in visual generation, flow-based models reemerge as another prominent family of generative models that have achieved competitive or bett…
DC-Solver: Improving Predictor-Corrector Diffusion Sampler via Dynamic Compensation
Wenliang Zhao, Haolin Wang, Jie Zhou +1
Diffusion probabilistic models (DPMs) have shown remarkable performance in visual synthesis but are computationally expensive due to the need for multiple evaluations during the sa…
EmbodiedSAM: Online Segment Any 3D Thing in Real Time
Xiuwei Xu, Huangxing Chen, Linqing Zhao +3
Embodied tasks require the agent to fully understand 3D scenes simultaneously with its exploration, so an online, real-time, fine-grained and highly-generalized 3D perception model…
FlowIE: Efficient Image Enhancement via Rectified Flow
Yixuan Zhu, Wenliang Zhao, Ao Li +3
Image enhancement holds extensive applications in real-world scenarios due to complex environments and limitations of imaging devices. Conventional methods are often constrained by…
Chain-of-Spot: Interactive Reasoning Improves Large Vision-Language Models
Zuyan Liu, Yuhao Dong, Yongming Rao +2
In the realm of vision-language understanding, the proficiency of models in interpreting and reasoning over visual content has become a cornerstone for numerous applications. Howev…
Memory-based Adapters for Online 3D Scene Perception
Xiuwei Xu, Chong Xia, Ziwei Wang +4
In this paper, we propose a new framework for online 3D scene perception. Conventional 3D scene perception methods are offline, i.e., take an already reconstructed 3D scene geometr…
Learning Dual-Level Deformable Implicit Representation for Real-World Scale Arbitrary Super-Resolution
Zhiheng Li, Muheng Li, Jixuan Fan +4
Scale arbitrary super-resolution based on implicit image function gains increasing popularity since it can better represent the visual world in a continuous manner. However, existi…
MCUFormer: Deploying Vision Transformers on Microcontrollers with Limited Memory
Yinan Liang, Ziwei Wang, Xiuwei Xu +3
Due to the high price and heavy energy consumption of GPUs, deploying deep models on IoT devices such as microcontrollers makes significant contributions for ecological AI. Convent…
Skip-Plan: Procedure Planning in Instructional Videos via Condensed Action Space Learning
Zhiheng Li, Wenjia Geng, Muheng Li +4
In this paper, we propose Skip-Plan, a condensed action space learning method for procedure planning in instructional videos. Current procedure planning methods all stick to the st…
Gait Recognition in the Wild: A Large-scale Benchmark and NAS-based Baseline
Xianda Guo, Zheng Zhu, Tian Yang +6
Gait benchmarks empower the research community to train and evaluate high-performance gait recognition systems. Even though growing efforts have been devoted to cross-view recognit…
Multi-View Partial (MVP) Point Cloud Challenge 2021 on Completion and Registration: Methods and Results
Liang Pan, Tong Wu, Zhongang Cai +26
As real-scanned point clouds are mostly partial due to occlusions and viewpoints, reconstructing complete 3D shapes based on incomplete observations becomes a fundamental problem f…