activity
20192025
most citedFlowFormer++: Masked Cost Volume Autoencoding for Pretraining Optical Flow Estimation

4 citations · 20 across the 15 of their papers we have counts for

collaborators

16 papers

cs.CV2025

Are Video Models Ready as Zero-Shot Reasoners? An Empirical Study with the MME-CoF Benchmark

Ziyu Guo, Xinyan Chen, Renrui Zhang +7

Recent video generation models can produce high-fidelity, temporally coherent videos, indicating that they may encode substantial world knowledge. Beyond realistic synthesis, they…

cs.CV2025

CodePlot-CoT: Mathematical Visual Reasoning by Thinking with Code-Driven Images

Chengqi Duan, Kaiyue Sun, Rongyao Fang +10

Recent advances in Large Language Models (LLMs) and Vision Language Models (VLMs) have shown significant progress in mathematical reasoning, yet they still face a critical bottlene…

cs.CL2025

LM-Searcher: Cross-domain Neural Architecture Search with LLMs via Unified Numerical Encoding

Yuxuan Hu, Jihao Liu, Ke Wang +7

Recent progress in Large Language Models (LLMs) has opened new avenues for solving complex optimization problems, including Neural Architecture Search (NAS). However, existing LLM-…

cs.CV2025

Lumina-Image 2.0: A Unified and Efficient Image Generative Framework

Qi Qin, Le Zhuo, Yi Xin +20

We introduce Lumina-Image 2.0, an advanced text-to-image generation framework that achieves significant progress compared to previous work, Lumina-Next. Lumina-Image 2.0 is built u…

cs.CV2024

Deep Reward Supervisions for Tuning Text-to-Image Diffusion Models

Xiaoshi Wu, Yiming Hao, Manyuan Zhang +5

Optimizing a text-to-image diffusion model with a given reward function is an important but underexplored research area. In this study, we propose Deep Reward Tuning (DRTune), an a…

cs.CV2024★ 1 cited

Motion-I2V: Consistent and Controllable Image-to-Video Generation with Explicit Motion Modeling

Xiaoyu Shi, Zhaoyang Huang, Fu-Yun Wang +9

We introduce Motion-I2V, a novel framework for consistent and controllable image-to-video generation (I2V). In contrast to previous methods that directly learn the complicated imag…

cs.CV2023

Towards Large-scale Masked Face Recognition

Manyuan Zhang, Bingqi Ma, Guanglu Song +3

During the COVID-19 coronavirus epidemic, almost everyone is wearing masks, which poses a huge challenge for deep learning-based face recognition algorithms. In this paper, we will…

cs.CV2023★ 1 cited

Decoupled DETR: Spatially Disentangling Localization and Classification for Improved End-to-End Object Detection

Manyuan Zhang, Guanglu Song, Yu Liu +1

The introduction of DETR represents a new paradigm for object detection. However, its decoder conducts classification and box localization using shared queries and cross-attention…

cs.CV2023★ 4 cited

FlowFormer++: Masked Cost Volume Autoencoding for Pretraining Optical Flow Estimation

Xiaoyu Shi, Zhaoyang Huang, Dasong Li +6

FlowFormer introduces a transformer architecture into optical flow estimation and achieves state-of-the-art performance. The core component of FlowFormer is the transformer-based c…

cs.CV2023★ 4 cited

VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow Estimation

Xiaoyu Shi, Zhaoyang Huang, Weikang Bian +7

We introduce VideoFlow, a novel optical flow estimation framework for videos. In contrast to previous methods that learn to estimate optical flow from two frames, VideoFlow concurr…

cs.CV2022

Towards Robust Face Recognition with Comprehensive Search

Manyuan Zhang, Guanglu Song, Yu Liu +1

Data cleaning, architecture, and loss function design are important factors contributing to high-performance face recognition. Previously, the research community tries to improve t…

cs.CV2020★ 4 cited

Discriminability Distillation in Group Representation Learning

Manyuan Zhang, Guanglu Song, Hang Zhou +1

Learning group representation is a commonly concerned issue in tasks where the basic unit is a group, set, or sequence. Previously, the research community tries to tackle it by agg…

cs.CV2020

Complementary Boundary Generator with Scale-Invariant Relation Modeling for Temporal Action Localization: Submission to ActivityNet Challenge 2020

Haisheng Su, Jinyuan Feng, Hao Shao +6

This technical report presents an overview of our solution used in the submission to ActivityNet Challenge 2020 Task 1 (\textbf{temporal action localization/detection}). Temporal a…

cs.CV2020★ 4 cited

1st place solution for AVA-Kinetics Crossover in AcitivityNet Challenge 2020

Siyu Chen, Junting Pan, Guanglu Song +6

This technical report introduces our winning solution to the spatio-temporal action localization track, AVA-Kinetics Crossover, in ActivityNet Challenge 2020. Our entry is mainly b…

cs.CV2020★ 2 cited

Top-1 Solution of Multi-Moments in Time Challenge 2019

Manyuan Zhang, Hao Shao, Guanglu Song +2

In this technical report, we briefly introduce the solutions of our team 'Efficient' for the Multi-Moments in Time challenge in ICCV 2019. We first conduct several experiments with…

cs.CV2019

Towards Flops-constrained Face Recognition

Yu Liu, Guanglu Song, Manyuan Zhang +3

Large scale face recognition is challenging especially when the computational budget is limited. Given a \textit{flops} upper bound, the key is to find the optimal neural network a…