activity
20202025
most citedNTIRE 2020 Challenge on Image Demoireing: Methods and Results

3 citations · 4 across the 5 of their papers we have counts for

collaborators

13 papers

cs.CV2025

Novel Category Discovery with X-Agent Attention for Open-Vocabulary Semantic Segmentation

Jiahao Li, Yang Lu, Yachao Zhang +3

Open-vocabulary semantic segmentation (OVSS) conducts pixel-level classification via text-driven alignment, where the domain discrepancy between base category training and open-voc…

cs.CV2025

SeqVLM: Proposal-Guided Multi-View Sequences Reasoning via VLM for Zero-Shot 3D Visual Grounding

Jiawen Lin, Shiran Bian, Yihang Zhu +4

3D Visual Grounding (3DVG) aims to localize objects in 3D scenes using natural language descriptions. Although supervised methods achieve higher accuracy in constrained settings, z…

cs.LG2024

Large Continual Instruction Assistant

Jingyang Qiao, Zhizhong Zhang, Xin Tan +3

Continual Instruction Tuning (CIT) is adopted to continually instruct Large Models to follow human intent data by data. It is observed that existing gradient update would heavily d…

cs.CV20241 cited

Data-free Distillation with Degradation-prompt Diffusion for Multi-weather Image Restoration

Pei Wang, Xiaotong Luo, Yuan Xie +1

Multi-weather image restoration has witnessed incredible progress, while the increasing model capacity and expensive data acquisition impair its applications in memory-limited devi…

cs.CV2024

Exploring the Untouched Sweeps for Conflict-Aware 3D Segmentation Pretraining

Tianfang Sun, Zhizhong Zhang, Xin Tan +2

LiDAR-camera 3D representation pretraining has shown significant promise for 3D perception tasks and related applications. However, two issues widely exist in this framework: 1) So…

cs.CV2024

Building a Strong Pre-Training Baseline for Universal 3D Large-Scale Perception

Haoming Chen, Zhizhong Zhang, Yanyun Qu +3

An effective pre-training framework with universal 3D representations is extremely desired in perceiving large-scale dynamic scenes. However, establishing such an ideal framework t…