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20222026
most citedTowards Domain-agnostic Depth Completion

4 citations · 4 across the 7 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

EponaV2: Driving World Model with Comprehensive Future Reasoning

Jiawei Xu, Zhizhou Zhong, Zhijian Shu +8

Data scaling plays a pivotal role in the pursuit of general intelligence. However, the prevailing perception-planning paradigm in autonomous driving relies heavily on expensive man…

cs.CV2026

Thinking with Geometry: Active Geometry Integration for Spatial Reasoning

Haoyuan Li, Qihang Cao, Tao Tang +6

Recent progress in spatial reasoning with Multimodal Large Language Models (MLLMs) increasingly leverages geometric priors from 3D encoders. However, most existing integration stra…

cs.CV2025

OmniGen: Unified Multimodal Sensor Generation for Autonomous Driving

Tao Tang, Enhui Ma, xia zhou +9

Autonomous driving has seen remarkable advancements, largely driven by extensive real-world data collection. However, acquiring diverse and corner-case data remains costly and inef…

cs.CV2025

RoboPearls: Editable Video Simulation for Robot Manipulation

Tao Tang, Likui Zhang, Youpeng Wen +9

The development of generalist robot manipulation policies has seen significant progress, driven by large-scale demonstration data across diverse environments. However, the high cos…

cs.CV2025

Does Your 3D Encoder Really Work? When Pretrain-SFT from 2D VLMs Meets 3D VLMs

Haoyuan Li, Yanpeng Zhou, Yufei Gao +7

Remarkable progress in 2D Vision-Language Models (VLMs) has spurred interest in extending them to 3D settings for tasks like 3D Question Answering, Dense Captioning, and Visual Gro…

cs.CV2022★ 4 cited

Towards Domain-agnostic Depth Completion

Guangkai Xu, Wei Yin, Jianming Zhang +4

Existing depth completion methods are often targeted at a specific sparse depth type and generalize poorly across task domains. We present a method to complete sparse/semi-dense, n…