activity
20162024
most citedTowards High-quality HDR Deghosting with Conditional Diffusion Models

17 citations · 66 across the 45 of their papers we have counts for

collaborators

45 papers

cs.CV2024

Weakly Supervised Video Anomaly Detection and Localization with Spatio-Temporal Prompts

Peng Wu, Xuerong Zhou, Guansong Pang +4

Current weakly supervised video anomaly detection (WSVAD) task aims to achieve frame-level anomalous event detection with only coarse video-level annotations available. Existing wo…

cs.CV2024

Task-Adapter: Task-specific Adaptation of Image Models for Few-shot Action Recognition

Congqi Cao, Yueran Zhang, Yating Yu +3

Existing works in few-shot action recognition mostly fine-tune a pre-trained image model and design sophisticated temporal alignment modules at feature level. However, simply fully…

cs.CV2024

A Plug-and-Play Method for Rare Human-Object Interactions Detection by Bridging Domain Gap

Lijun Zhang, Wei Suo, Peng Wang +1

Human-object interactions (HOI) detection aims at capturing human-object pairs in images and corresponding actions. It is an important step toward high-level visual reasoning and s…

cs.CV2024

Visual Prompt Selection for In-Context Learning Segmentation

Wei Suo, Lanqing Lai, Mengyang Sun +3

As a fundamental and extensively studied task in computer vision, image segmentation aims to locate and identify different semantic concepts at the pixel level. Recently, inspired…

cs.CV2024

Indoor 3D Reconstruction with an Unknown Camera-Projector Pair

Zhaoshuai Qi, Yifeng Hao, Rui Hu +3

Structured light-based method with a camera-projector pair (CPP) plays a vital role in indoor 3D reconstruction, especially for scenes with weak textures. Previous methods usually…

cs.CV2024

C3L: Content Correlated Vision-Language Instruction Tuning Data Generation via Contrastive Learning

Ji Ma, Wei Suo, Peng Wang +1

Vision-Language Instruction Tuning (VLIT) is a critical training phase for Large Vision-Language Models (LVLMs). With the improving capabilities of open-source LVLMs, researchers h…