5 citations · 12 across the 10 of their papers we have counts for
10 papers
Illuminating Unified Multimodal Model for Free-form Interleaved Text-Image Generation
Chonghuinan Wang, Zhikai Chen, Chunwei Wang +9
The advancement of generative AI models capable of producing text and image marks a critical step forward in the realm of multimodal intelligence, particularly for tasks involving…
SplatWeaver: Learning to Allocate Gaussian Primitives for Generalizable Novel View Synthesis
Yecong Wan, Fan Li, Mingwen Shao +1
Generalizable novel view synthesis aims to render unseen views from uncalibrated input images without requiring per-scene optimization. Recent feed-forward approaches based on 3D G…
InterCoG: Towards Spatially Precise Image Editing with Interleaved Chain-of-Grounding Reasoning
Yecong Wan, Fan Li, Chunwei Wang +3
Emerging unified editing models have demonstrated strong capabilities in general object editing tasks. However, it remains a significant challenge to perform fine-grained editing i…
Color3D: Controllable and Consistent 3D Colorization with Personalized Colorizer
Yecong Wan, Mingwen Shao, Renlong Wu +1
In this work, we present Color3D, a highly adaptable framework for colorizing both static and dynamic 3D scenes from monochromatic inputs, delivering visually diverse and chromatic…
Removing Multiple Hybrid Adverse Weather in Video via a Unified Model
Yecong Wan, Mingwen Shao, Yuanshuo Cheng +2
Videos captured under real-world adverse weather conditions typically suffer from uncertain hybrid weather artifacts with heterogeneous degradation distributions. However, existing…
S2Gaussian: Sparse-View Super-Resolution 3D Gaussian Splatting
Yecong Wan, Mingwen Shao, Yuanshuo Cheng +1
In this paper, we aim ambitiously for a realistic yet challenging problem, namely, how to reconstruct high-quality 3D scenes from sparse low-resolution views that simultaneously su…
Cross-Consistent Deep Unfolding Network for Adaptive All-In-One Video Restoration
Yuanshuo Cheng, Mingwen Shao, Yecong Wan +3
Existing Video Restoration (VR) methods always necessitate the individual deployment of models for each adverse weather to remove diverse adverse weather degradations, lacking the…
DRM-IR: Task-Adaptive Deep Unfolding Network for All-In-One Image Restoration
Yuanshuo Cheng, Mingwen Shao, Yecong Wan +1
Existing All-In-One image restoration (IR) methods usually lack flexible modeling on various types of degradation, thus impeding the restoration performance. To achieve All-In-One…
Restoring Images Captured in Arbitrary Hybrid Adverse Weather Conditions in One Go
Ye-Cong Wan, Ming-Wen Shao, Yuan-Shuo Cheng +2
Adverse conditions typically suffer from stochastic hybrid weather degradations (e.g., rainy and hazy night), while existing image restoration algorithms envisage that weather degr…
Rain Removal and Illumination Enhancement Done in One Go
Yecong Wan, Yuanshuo Cheng, Mingwen Shao
Rain removal plays an important role in the restoration of degraded images. Recently, data-driven methods have achieved remarkable success. However, these approaches neglect that t…