51 citations · 69 across the 36 of their papers we have counts for
35 papers · 1 filter
RegVGGT: Sustainable Visual Geometry Grounding for Streaming via Regulated Memory
Hongbo Mao, Junjun Jiang, Youyu Chen +3
3D reconstruction from a lengthy video stream input poses a dilemma for feed-forward reconstruction models (FFRMs), that a whole-stream inference context cannot be retained under l…
ViP-Rig: Visual-Prompted Controllable Rigging
Zihan Qin, Mingze Sun, Yifan Mao +6
Rigging is inherently task-dependent because the same mesh may require different skeletons and deformation behaviors across animation tasks. In practice, artists often inspect an i…
RainDancer: RGB-Event Video Deraining with Rain-Oriented Spiking Dynamics
Kui Jiang, Runzhe Li, Zhaocheng Yu +3
Video deraining aims to recover clean visual content from rainy videos for reliable perception under adverse weather. Existing methods mainly rely on RGB sequences and temporal red…
Reliev3R: Relieving Feed-forward Reconstruction from Multi-View Geometric Annotations
Youyu Chen, Junjun Jiang, Yueru Luo +4
With recent advances, Feed-forward Reconstruction Models (FFRMs) have demonstrated great potential in reconstruction quality and adaptiveness to multiple downstream tasks. However,…
Focus-Scan-Refine: From Human Visual Perception to Efficient Visual Token Pruning
Enwei Tong, Yuanchao Bai, Yao Zhu +2
Vision-language models (VLMs) often generate massive visual tokens that greatly increase inference latency and memory footprint; while training-free token pruning offers a practica…
UDPNet: Unleashing Depth-based Priors for Robust Image Dehazing
Zengyuan Zuo, Junjun Jiang, Gang Wu +1
Image dehazing has witnessed significant advancements with the development of deep learning models. However, most existing methods focus solely on single-modal RGB features, neglec…
Semantics and Content Matter: Towards Multi-Prior Hierarchical Mamba for Image Deraining
Zhaocheng Yu, Kui Jiang, Junjun Jiang +3
Rain significantly degrades the performance of computer vision systems, particularly in applications like autonomous driving and video surveillance. While existing deraining method…
Rethinking Autoregressive Models for Lossless Image Compression via Hierarchical Parallelism and Progressive Adaptation
Daxin Li, Yuanchao Bai, Kai Wang +3
Autoregressive (AR) models, the theoretical performance benchmark for learned lossless image compression, are often dismissed as impractical due to prohibitive computational cost.…
Boosting All-in-One Image Restoration via Self-Improved Privilege Learning
Gang Wu, Junjun Jiang, Kui Jiang +1
Unified image restoration models for diverse and mixed degradations often suffer from unstable optimization dynamics and inter-task conflicts. This paper introduces Self-Improved P…
The Fourth Monocular Depth Estimation Challenge
Anton Obukhov, Matteo Poggi, Fabio Tosi +54
This paper presents the results of the fourth edition of the Monocular Depth Estimation Challenge (MDEC), which focuses on zero-shot generalization to the SYNS-Patches benchmark, a…
Beyond Degradation Redundancy: Contrastive Prompt Learning for All-in-One Image Restoration
Gang Wu, Junjun Jiang, Kui Jiang +2
All-in-One Image Restoration (AiOIR), which addresses diverse degradation types with a unified model, presents significant challenges in designing task-aware prompts that effective…
Balancing Task-invariant Interaction and Task-specific Adaptation for Unified Image Fusion
Xingyu Hu, Junjun Jiang, Chenyang Wang +3
Unified image fusion aims to integrate complementary information from multi-source images, enhancing image quality through a unified framework applicable to diverse fusion tasks. W…
DSwinIR: Rethinking Window-based Attention for Image Restoration
Gang Wu, Junjun Jiang, Kui Jiang +2
Image restoration has witnessed significant advancements with the development of deep learning models. Transformer-based models, particularly those using window-based self-attentio…
COB-GS: Clear Object Boundaries in 3DGS Segmentation Based on Boundary-Adaptive Gaussian Splitting
Jiaxin Zhang, Junjun Jiang, Youyu Chen +2
Accurate object segmentation is crucial for high-quality scene understanding in the 3D vision domain. However, 3D segmentation based on 3D Gaussian Splatting (3DGS) struggles with…
DashGaussian: Optimizing 3D Gaussian Splatting in 200 Seconds
Youyu Chen, Junjun Jiang, Kui Jiang +4
3D Gaussian Splatting (3DGS) renders pixels by rasterizing Gaussian primitives, where the rendering resolution and the primitive number, concluded as the optimization complexity, d…
FUSE: Label-Free Image-Event Joint Monocular Depth Estimation via Frequency-Decoupled Alignment and Degradation-Robust Fusion
Pihai Sun, Junjun Jiang, Yuanqi Yao +4
Image-event joint depth estimation methods leverage complementary modalities for robust perception, yet face challenges in generalizability stemming from two factors: 1) limited an…
CALLIC: Content Adaptive Learning for Lossless Image Compression
Daxin Li, Yuanchao Bai, Kai Wang +3
Learned lossless image compression has achieved significant advancements in recent years. However, existing methods often rely on training amortized generative models on massive da…
Adaptive Stereo Depth Estimation with Multi-Spectral Images Across All Lighting Conditions
Zihan Qin, Jialei Xu, Wenbo Zhao +2
Depth estimation under adverse conditions remains a significant challenge. Recently, multi-spectral depth estimation, which integrates both visible light and thermal images, has sh…
Improving Domain Generalization in Self-supervised Monocular Depth Estimation via Stabilized Adversarial Training
Yuanqi Yao, Gang Wu, Kui Jiang +4
Learning a self-supervised Monocular Depth Estimation (MDE) model with great generalization remains significantly challenging. Despite the success of adversarial augmentation in th…
A Survey on All-in-One Image Restoration: Taxonomy, Evaluation and Future Trends
Junjun Jiang, Zengyuan Zuo, Gang Wu +2
Image restoration (IR) seeks to recover high-quality images from degraded observations caused by a wide range of factors, including noise, blur, compression, and adverse weather. W…
MCGS: Multiview Consistency Enhancement for Sparse-View 3D Gaussian Radiance Fields
Yuru Xiao, Deming Zhai, Wenbo Zhao +3
Radiance fields represented by 3D Gaussians excel at synthesizing novel views, offering both high training efficiency and fast rendering. However, with sparse input views, the lack…
PVContext: Hybrid Context Model for Point Cloud Compression
Guoqing Zhang, Wenbo Zhao, Jian Liu +3
Efficient storage of large-scale point cloud data has become increasingly challenging due to advancements in scanning technology. Recent deep learning techniques have revolutionize…
MIPI 2024 Challenge on Few-shot RAW Image Denoising: Methods and Results
Xin Jin, Chunle Guo, Xiaoming Li +39
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algor…
Spatial Annealing for Efficient Few-shot Neural Rendering
Yuru Xiao, Deming Zhai, Wenbo Zhao +3
Neural Radiance Fields (NeRF) with hybrid representations have shown impressive capabilities for novel view synthesis, delivering high efficiency. Nonetheless, their performance si…