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20192026
most citedRobust Lane Detection from Continuous Driving Scenes Using Deep Neural Networks

358 citations · 387 across the 27 of their papers we have counts for

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8 papers · 1 filter

cs.CV2026

StableGrasp: Reconstructing Physically Stable Human Hand Grasps from Single Images

Han Jiang, Etienne Vouga, Qixing Huang +1

Reconstructing a physically stable human grasp from a single RGB image is challenging because physically modeling grasps is itself difficult, and the problem requires estimating no…

cs.LG2026

Learning Length-Extrapolatable Recurrent Models

Hanwen Jiang

Recurrent models provide a natural path to long-context modeling, yet models trained with backpropagation through time (BPTT) often fail beyond their training horizon. Classical an…

cs.LG2026

Revisiting Spectral Representations in Generative Diffusion Models

Yuehao Wang, Peihao Wang, Hanwen Jiang +3

Diffusion models have shown remarkable performance on diverse generation tasks. Recent work finds that imposing representation alignment on the hidden states of diffusion networks…

cs.CV2026

Chimera: Designing and Chinchilla-Scaling Hybrid Visual Diffusion Transformers

Chongjian Ge, Hanwen Jiang, Tianyu Wang +9

Visual generation increasingly requires high-resolution images, long videos, and multimodal context, making the quadratic cost of full attention prohibitive. We introduce Chimera,…

cs.CV2026

Wonder: Video World Model Done Better

Jiacong Xu, Hanwen Jiang, Zhixin Shu +3

We present Wonder, a general-purpose video world model for real-time, camera-controllable world exploration. Given an image or a conditional video, Wonder constructs a playable wor…

cs.CV2026

HumanNOVA: Photorealistic, Universal and Rapid 3D Human Avatar Modeling from a Single Image

Hezhen Hu, Wangbo Zhao, Lanqing Guo +6

In this paper, we present HumanNOVA, a photorealistic, universal, and rapid model for generating 3D human avatars from a single RGB image. Achieving both photorealism and generaliz…

cs.CV2026

Mining Attribute Subspaces for Efficient Fine-tuning of 3D Foundation Models

Yu Jiang, Hanwen Jiang, Ahmed Abdelkader +4

With the emergence of 3D foundation models, there is growing interest in fine-tuning them for downstream tasks, where LoRA is the dominant fine-tuning paradigm. As 3D datasets exhi…

cs.CV2026

MotiMotion: Motion-Controlled Video Generation with Visual Reasoning

Lee Hsin-Ying, Hanwen Jiang, Yiqun Mei +3

Current motion-controlled image-to-video generation models rigidly follow user-provided trajectories that are often sparse, imprecise, and causally incomplete. Such reliance often…