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From the 1 of 5 linked papers with an AI index.

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5 papers

cs.CV2026

ROAD: Reciprocal-Objective Alignment of Discriminative Semantics for 3D Shape Generation

Xiao Luo, Mingyang Du, Xin Zhou +5

The paper introduces ROAD, a framework that transfers semantic and structural knowledge from discriminative 3D foundation models into diffusion transformers for 3D shape generation…

cs.CV2026

Generation Models Know Space: Unleashing Implicit 3D Priors for Scene Understanding

Xianjin Wu, Dingkang Liang, Tianrui Feng +5

While Multimodal Large Language Models demonstrate impressive semantic capabilities, they often suffer from spatial blindness, struggling with fine-grained geometric reasoning and…

cs.CV2026

When Numbers Speak: Aligning Textual Numerals and Visual Instances in Text-to-Video Diffusion Models

Zhengyang Sun, Yu Chen, Xin Zhou +4

Text-to-video diffusion models have enabled open-ended video synthesis, but often struggle with generating the correct number of objects specified in a prompt. We introduce NUMINA…

cs.CV2026

UniFuture: A 4D Driving World Model for Future Generation and Perception

Dingkang Liang, Dingyuan Zhang, Xin Zhou +7

We present UniFuture, a unified 4D Driving World Model designed to simulate the dynamic evolution of the 3D physical world. Unlike existing driving world models that focus solely o…

cs.CV2026

The Role of World Models in Shaping Autonomous Driving: A Comprehensive Survey

Sifan Tu, Xin Zhou, Dingkang Liang +4

The Driving World Model (DWM), which focuses on predicting scene evolution during the driving process, has emerged as a promising paradigm in the pursuit of autonomous driving (AD)…