1 citations · 3 across the 13 of their papers we have counts for
15 papers
DICS: Exploring Data Intrinsic Consistency for Visual Instruction Selection
Yuyang Hong, Jinhui Guo, Jiaqi Gu +6
Visual instruction tuning is crucial for advancing the vision-language alignment and instruction-following capabilities of Vision-Language Models (VLMs). However, identifying optim…
DiffPDE: Masked Diffusion Language Models as PDE Solver
Wenxuan Guo, Yuyang Hong, Lubin Fan +4
Existing approaches for synthesizing Partial Differential Equation (PDE) solvers predominantly rely on autoregressive models, yet their global left-to-right decoding incurs substan…
CC-VQA: Conflict- and Correlation-Aware Method for Mitigating Knowledge Conflict in Knowledge-Based Visual Question Answering
Yuyang Hong, Jiaqi Gu, Yujin Lou +7
Knowledge-based visual question answering (KB-VQA) demonstrates significant potential for handling knowledge-intensive tasks. However, conflicts arise between static parametric kno…
Sketch-in-Latents: Eliciting Unified Reasoning in MLLMs
Jintao Tong, Jiaqi Gu, Yujing Lou +5
While Multimodal Large Language Models (MLLMs) excel at visual understanding tasks through text reasoning, they often fall short in scenarios requiring visual imagination. Unlike c…
NoPe-NeRF++: Local-to-Global Optimization of NeRF with No Pose Prior
Dongbo Shi, Shen Cao, Bojian Wu +5
In this paper, we introduce NoPe-NeRF++, a novel local-to-global optimization algorithm for training Neural Radiance Fields (NeRF) without requiring pose priors. Existing methods,…
Knowledge-based Visual Question Answer with Multimodal Processing, Retrieval and Filtering
Yuyang Hong, Jiaqi Gu, Qi Yang +6
Knowledge-based visual question answering (KB-VQA) requires visual language models (VLMs) to integrate visual understanding with external knowledge retrieval. Although retrieval-au…
SD-VLM: Spatial Measuring and Understanding with Depth-Encoded Vision-Language Models
Pingyi Chen, Yujing Lou, Shen Cao +6
While vision language models (VLMs) excel in 2D semantic visual understanding, their ability to quantitatively reason about 3D spatial relationships remains under-explored, due to…
AddressVLM: Cross-view Alignment Tuning for Image Address Localization using Large Vision-Language Models
Shixiong Xu, Chenghao Zhang, Lubin Fan +5
Large visual language models (LVLMs) have demonstrated impressive performance in coarse-grained geo-localization at the country or city level, but they struggle with fine-grained s…
Re-ranking Reasoning Context with Tree Search Makes Large Vision-Language Models Stronger
Qi Yang, Chenghao Zhang, Lubin Fan +3
Recent advancements in Large Vision Language Models (LVLMs) have significantly improved performance in Visual Question Answering (VQA) tasks through multimodal Retrieval-Augmented…
PTZ-Calib: Robust Pan-Tilt-Zoom Camera Calibration
Jinhui Guo, Lubin Fan, Bojian Wu +3
In this paper, we present PTZ-Calib, a robust two-stage PTZ camera calibration method, that efficiently and accurately estimates camera parameters for arbitrary viewpoints. Our met…
CoL3D: Collaborative Learning of Single-view Depth and Camera Intrinsics for Metric 3D Shape Recovery
Chenghao Zhang, Lubin Fan, Shen Cao +2
Recovering the metric 3D shape from a single image is particularly relevant for robotics and embodied intelligence applications, where accurate spatial understanding is crucial for…
TrackGS: Optimizing COLMAP-Free 3D Gaussian Splatting with Global Track Constraints
Dongbo Shi, Shen Cao, Lubin Fan +4
We present TrackGS, a novel method to integrate global feature tracks with 3D Gaussian Splatting (3DGS) for COLMAP-free novel view synthesis. While 3DGS delivers impressive renderi…
HybridGS: Decoupling Transients and Statics with 2D and 3D Gaussian Splatting
Jingyu Lin, Jiaqi Gu, Lubin Fan +5
Generating high-quality novel view renderings of 3D Gaussian Splatting (3DGS) in scenes featuring transient objects is challenging. We propose a novel hybrid representation, termed…
AddressCLIP: Empowering Vision-Language Models for City-wide Image Address Localization
Shixiong Xu, Chenghao Zhang, Lubin Fan +3
In this study, we introduce a new problem raised by social media and photojournalism, named Image Address Localization (IAL), which aims to predict the readable textual address whe…
Learning Neural Volumetric Pose Features for Camera Localization
Jingyu Lin, Jiaqi Gu, Bojian Wu +4
We introduce a novel neural volumetric pose feature, termed PoseMap, designed to enhance camera localization by encapsulating the information between images and the associated came…