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Works68 from public data
- Single-Model and Any-Modality for Video Object Tracking172
This work introduces Un-Track, a Unified Tracker of a single set of parameters for any modality, which surpasses both SOTA unified trackers and modality-specific counterparts, validating the effectiveness and practicality.
- HiDAnet: RGB-D Salient Object Detection via Hierarchical Depth Awareness158
This paper proposes a novel Hierarchical Depth Awareness network (HiDAnet) for RGB-D saliency detection, and uses a granularity-based attention scheme to strengthen the discriminatory power of RGB and depth features separately and introduces a unified cross dual-attention module for multi-modal and multi-level fusion in a coarse-to-fine manner.
- Source-free Depth for Object Pop-out142
This work adapts depth inference models for object segmentation using the objects’ "pop-out" prior in 3D to adapt the inferred depth maps such that objects can be localized using only 3D information.
- Complexity Experts are Task-Discriminative Learners for Any Image Restoration128
The proposed MoCE-IR model outperforms state-of-the-art methods, affirming its efficiency and practical applicability and introducing “complexity experts” – flexible expert blocks with varying computational complexity and receptive fields.
- RGB-Event Fusion for Moving Object Detection in Autonomous Driving102
RENet is a novel RGB-Event fusion Network that jointly exploits the two complementary modalities to achieve more robust MOD under challenging scenarios for autonomous driving and performs significantly better than the state-of-the-art RGB- event fusion alternatives.
- NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results85
This paper meticulously evaluates the state-of-the-art advancements in enhancing low-light images, reflecting the significant progress and creativity in this field.
- NTIRE 2024 Challenge on Image Super-Resolution (×4): Methods and Results83
This paper reviews the NTIRE 2024 challenge on image super-resolution (×4), highlighting the solutions proposed and the outcomes obtained, and offers a comprehensive overview of current trends in this field.
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- See More Details: Efficient Image Super-Resolution by Experts Mining51
This work introduces SeemoRe, an efficient SR model employing expert mining, strategically incorporates experts at different levels, adopting a collaborative methodology, allowing the model to achieve an optimal performance with minimal computational costs in efficient settings.
- Rethinking Few-shot 3D Point Cloud Semantic Segmentation50
This paper revisits few-shot 3D point cloud semantic segmentation (FS-PCS), with a focus on two significant is-sues in the state-of-the-art: foreground leakage and sparse point distribution, and proposes a novel FS-PCS model based on correlation optimization, referred to as Correlation Optimization Segmentation (COSeg).
- Robust RGB-D Fusion for Saliency Detection48
This work proposes a robust RGB-D fusion method that benefits from layer-wise, and trident spatial, attention mechanisms, and demonstrates that the proposed fusion method performs consistently better than the state-of-the-art fusion alternatives.
- Object Segmentation by Mining Cross-Modal Semantics47
A novel approach by mining the Cross-Modal Semantics to guide the fusion and decoding of multimodal features, with the aim of controlling the modal contribution based on relative entropy.
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- The Tenth NTIRE 2025 Efficient Super-Resolution Challenge Report39
This paper presents a comprehensive review of the NTIRE 2025 Challenge on Single-Image Efficient Super-Resolution, emphasizing groundbreaking advancements in state-of-the-art single-image ESR techniques.
- Event-Based Eye Tracking. AIS 2024 Challenge Survey38
This survey reviews the AIS 2024 Event-Based Eye Tracking (EET) Challenge and examines novel and diverse methods from the submitted factsheets to advance future event-based eye tracking research.
- NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results37
This paper reviews the NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images to establish a new and powerful benchmark for the task of removing raindrops under varying lighting and focus conditions.
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- NTIRE 2025 Challenge on Low Light Image Enhancement: Methods and Results29
This paper thoroughly evaluates the state-of-the-art advancements in LLIE, showcasing the significant progress.
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- CamDiff: Camouflage Image Augmentation via Diffusion Model28
CamDiff is introduced, a novel approach inspired by AI-Generated Content that overcomes the scarcity of multi-pattern training images and significantly enhances COD baselines' training and testing phases, emphasizing robustness across diverse domains.
- The Eleventh NTIRE 2026 Efficient Super-Resolution Challenge Report27
This paper reviews the NTIRE 2026 challenge on efficient single-image super-resolution with a focus on the proposed solutions and results and gauges the state-of-the-art results for efficient single-image super-resolution.
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- NTIRE 2025 Challenge on Image Super-Resolution ($\times 4$): Methods and Results23
The NTIRE 2025 image super-resolution ($\times 4$) challenge, one of the associated competitions of the 10th NTIRE Workshop at CVPR 2025, aims to recover high-resolution images from low-resolution counterparts generated through bicubic downsampling with a $\times 4$ scaling factor.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-12. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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