most citedPTZ-Calib: Robust Pan-Tilt-Zoom Camera Calibration

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cs.CV2026

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…