57 citations · 236 across the 22 of their papers we have counts for
24 papers
Dynamic-Robust Photometric-Semantic Reconstruction for Open-Vocabulary 3D Scene Understanding
Boyu Cai, Li Yang, Yan Xu +6
The integration of novel view synthesis (NVS) and open-vocabulary segmentation (OVS) has recently yielded powerful feed-forward 3D foundation models. However, their inherent relian…
Gaze-DETR: Top-Down Guidance Through Priority Maps for Infrared Weak-Small UAV Detection with DETR
Nian Liu, Yuxin Yang, Shubo Lin +6
Infrared small target detection (ISTD) remains challenging because tiny, low-contrast targets are easily overwhelmed by clutter, noise, or occlusion. Conventional single-frame and…
MI-DETR: A Strong Baseline for Moving Infrared Small Target Detection with Motion Integration
Nian Liu, Jin Gao, Shubo Lin +9
Detecting moving infrared small targets is challenging because tiny, low-contrast targets occupy few pixels and are easily obscured by dynamic backgrounds. Existing multi-frame met…
VSCode: General Visual Salient and Camouflaged Object Detection with 2D Prompt Learning
Ziyang Luo, Nian Liu, Wangbo Zhao +5
Salient object detection (SOD) and camouflaged object detection (COD) are related yet distinct binary mapping tasks. These tasks involve multiple modalities, sharing commonalities…
GP-NeRF: Generalized Perception NeRF for Context-Aware 3D Scene Understanding
Hao Li, Dingwen Zhang, Yalun Dai +5
Applying NeRF to downstream perception tasks for scene understanding and representation is becoming increasingly popular. Most existing methods treat semantic prediction as an addi…
VST++: Efficient and Stronger Visual Saliency Transformer
Nian Liu, Ziyang Luo, Ni Zhang +1
While previous CNN-based models have exhibited promising results for salient object detection (SOD), their ability to explore global long-range dependencies is restricted. Our prev…
Multi-grained Temporal Prototype Learning for Few-shot Video Object Segmentation
Nian Liu, Kepan Nan, Wangbo Zhao +7
Few-Shot Video Object Segmentation (FSVOS) aims to segment objects in a query video with the same category defined by a few annotated support images. However, this task was seldom…
CalibNet: Dual-branch Cross-modal Calibration for RGB-D Salient Instance Segmentation
Jialun Pei, Tao Jiang, He Tang +4
We propose a novel approach for RGB-D salient instance segmentation using a dual-branch cross-modal feature calibration architecture called CalibNet. Our method simultaneously cali…
Discriminative Co-Saliency and Background Mining Transformer for Co-Salient Object Detection
Long Li, Junwei Han, Ni Zhang +5
Most previous co-salient object detection works mainly focus on extracting co-salient cues via mining the consistency relations across images while ignoring explicit exploration of…
Boosting Low-Data Instance Segmentation by Unsupervised Pre-training with Saliency Prompt
Hao Li, Dingwen Zhang, Nian Liu +5
Recently, inspired by DETR variants, query-based end-to-end instance segmentation (QEIS) methods have outperformed CNN-based models on large-scale datasets. Yet they would lose eff…
Intermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation
Yuanwei Liu, Nian Liu, Xiwen Yao +1
Few-shot semantic segmentation aims to segment the target objects in query under the condition of a few annotated support images. Most previous works strive to mine more effective…
Structured Attention Composition for Temporal Action Localization
Le Yang, Junwei Han, Tao Zhao +2
Temporal action localization aims at localizing action instances from untrimmed videos. Existing works have designed various effective modules to precisely localize action instance…
Learning Non-target Knowledge for Few-shot Semantic Segmentation
Yuanwei Liu, Nian Liu, Qinglong Cao +3
Existing studies in few-shot semantic segmentation only focus on mining the target object information, however, often are hard to tell ambiguous regions, especially in non-target r…
Light Field Saliency Detection with Dual Local Graph Learning andReciprocative Guidance
Nian Liu, Wangbo Zhao, Dingwen Zhang +2
The application of light field data in salient object de-tection is becoming increasingly popular recently. The diffi-culty lies in how to effectively fuse the features within the…
Summarize and Search: Learning Consensus-aware Dynamic Convolution for Co-Saliency Detection
Ni Zhang, Junwei Han, Nian Liu +1
Humans perform co-saliency detection by first summarizing the consensus knowledge in the whole group and then searching corresponding objects in each image. Previous methods usuall…
Instance-Level Relative Saliency Ranking with Graph Reasoning
Nian Liu, Long Li, Wangbo Zhao +2
Conventional salient object detection models cannot differentiate the importance of different salient objects. Recently, two works have been proposed to detect saliency ranking by…
Context-aware Cross-level Fusion Network for Camouflaged Object Detection
Yujia Sun, Geng Chen, Tao Zhou +2
Camouflaged object detection (COD) is a challenging task due to the low boundary contrast between the object and its surroundings. In addition, the appearance of camouflaged object…
Weakly Supervised Video Salient Object Detection
Wangbo Zhao, Jing Zhang, Long Li +3
Significant performance improvement has been achieved for fully-supervised video salient object detection with the pixel-wise labeled training datasets, which are time-consuming an…
Visual Saliency Transformer
Nian Liu, Ni Zhang, Kaiyuan Wan +2
Existing state-of-the-art saliency detection methods heavily rely on CNN-based architectures. Alternatively, we rethink this task from a convolution-free sequence-to-sequence persp…
Salient Object Detection via Integrity Learning
Mingchen Zhuge, Deng-Ping Fan, Nian Liu +3
Although current salient object detection (SOD) works have achieved significant progress, they are limited when it comes to the integrity of the predicted salient regions. We defin…
Learning Selective Mutual Attention and Contrast for RGB-D Saliency Detection
Nian Liu, Ni Zhang, Ling Shao +1
How to effectively fuse cross-modal information is the key problem for RGB-D salient object detection. Early fusion and the result fusion schemes fuse RGB and depth information at…
PiCANet: Pixel-wise Contextual Attention Learning for Accurate Saliency Detection
Nian Liu, Junwei Han, Ming-Hsuan Yang
In saliency detection, every pixel needs contextual information to make saliency prediction. Previous models usually incorporate contexts holistically. However, for each pixel, usu…
PiCANet: Learning Pixel-wise Contextual Attention for Saliency Detection
Nian Liu, Junwei Han, Ming-Hsuan Yang
Contexts play an important role in the saliency detection task. However, given a context region, not all contextual information is helpful for the final task. In this paper, we pro…
A Deep Spatial Contextual Long-term Recurrent Convolutional Network for Saliency Detection
Nian Liu, Junwei Han
Traditional saliency models usually adopt hand-crafted image features and human-designed mechanisms to calculate local or global contrast. In this paper, we propose a novel computa…