3 citations · 5 across the 15 of their papers we have counts for
16 papers
LensStyle: Learning the Optical Aesthetics for Controllable Stylized Lens Effect Rendering
Yachuan Huang, Liwen Xiao, Liao Shen +4
The visual aesthetics of photographs are deeply influenced by lens characteristics such as aperture shape, optical vignetting and optical diffraction, which together define a camer…
Compression and Retrieval: Implicit Memory Retrieval for Video World Models
Zhan Peng, Jie Ma, Huiqiang Sun +6
Video world models hold promise for simulating interactive environments, yet maintaining consistent long-term memory across complex camera trajectories remains a critical challenge…
Through the Lens of Contrast: Self-Improving Visual Reasoning in VLMs
Zhiyu Pan, Yizheng Wu, Jiashen Hua +5
Reasoning has emerged as a key capability of large language models. In linguistic tasks, this capability can be enhanced by self-improving techniques that refine reasoning paths fo…
Semi-Supervised High Dynamic Range Image Reconstructing via Bi-Level Uncertain Area Masking
Wei Jiang, Jiahao Cui, Yizheng Wu +3
Reconstructing high dynamic range (HDR) images from low dynamic range (LDR) bursts plays an essential role in the computational photography. Impressive progress has been achieved b…
SRefiner: Soft-Braid Attention for Multi-Agent Trajectory Refinement
Liwen Xiao, Zhiyu Pan, Zhicheng Wang +2
Accurate prediction of multi-agent future trajectories is crucial for autonomous driving systems to make safe and efficient decisions. Trajectory refinement has emerged as a key st…
Dynamic View Synthesis from Small Camera Motion Videos
Huiqiang Sun, Xingyi Li, Juewen Peng +4
Novel view synthesis for dynamic D scenes poses a significant challenge. Many notable efforts use NeRF-based approaches to address this task and yield impressive results. Howeve…
TacoDepth: Towards Efficient Radar-Camera Depth Estimation with One-stage Fusion
Yiran Wang, Jiaqi Li, Chaoyi Hong +6
Radar-Camera depth estimation aims to predict dense and accurate metric depth by fusing input images and Radar data. Model efficiency is crucial for this task in pursuit of real-ti…
Exploring Contextual Attribute Density in Referring Expression Counting
Zhicheng Wang, Zhiyu Pan, Zhan Peng +4
Referring expression counting (REC) algorithms are for more flexible and interactive counting ability across varied fine-grained text expressions. However, the requirement for fine…
Deblur-Avatar: Animatable Avatars from Motion-Blurred Monocular Videos
Xianrui Luo, Juewen Peng, Zhongang Cai +4
We introduce a novel framework for modeling high-fidelity, animatable 3D human avatars from motion-blurred monocular video inputs. Motion blur is prevalent in real-world dynamic vi…
Exposure Completing for Temporally Consistent Neural High Dynamic Range Video Rendering
Jiahao Cui, Wei Jiang, Zhan Peng +2
High dynamic range (HDR) video rendering from low dynamic range (LDR) videos where frames are of alternate exposure encounters significant challenges, due to the exposure change an…
iControl3D: An Interactive System for Controllable 3D Scene Generation
Xingyi Li, Yizheng Wu, Jun Cen +6
3D content creation has long been a complex and time-consuming process, often requiring specialized skills and resources. While recent advancements have allowed for text-guided 3D…
Dynamic Neural Radiance Field From Defocused Monocular Video
Xianrui Luo, Huiqiang Sun, Juewen Peng +1
Dynamic Neural Radiance Field (NeRF) from monocular videos has recently been explored for space-time novel view synthesis and achieved excellent results. However, defocus blur caus…
Pseudo-Labeling by Multi-Policy Viewfinder Network for Image Cropping
Zhiyu Pan, Kewei Wang, Yizheng Wu +4
Automatic image cropping models predict reframing boxes to enhance image aesthetics. Yet, the scarcity of labeled data hinders the progress of this task. To overcome this limitatio…
Instance Consistency Regularization for Semi-Supervised 3D Instance Segmentation
Yizheng Wu, Zhiyu Pan, Kewei Wang +5
Large-scale datasets with point-wise semantic and instance labels are crucial to 3D instance segmentation but also expensive. To leverage unlabeled data, previous semi-supervised 3…
Self-Supervised Class-Agnostic Motion Prediction with Spatial and Temporal Consistency Regularizations
Kewei Wang, Yizheng Wu, Jun Cen +5
The perception of motion behavior in a dynamic environment holds significant importance for autonomous driving systems, wherein class-agnostic motion prediction methods directly pr…
Semi-Supervised Class-Agnostic Motion Prediction with Pseudo Label Regeneration and BEVMix
Kewei Wang, Yizheng Wu, Zhiyu Pan +5
Class-agnostic motion prediction methods aim to comprehend motion within open-world scenarios, holding significance for autonomous driving systems. However, training a high-perform…