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Junfei Xiao

14 accepted papers

2026

Captain Cinema: Towards Short Movie Generation

ICLR 2026poster

We present **Captain Cinema**, a generation framework for short movie generation. Given a detailed textual description of a movie storyline, our approach firstly generates a sequence of keyframes that outline the entire narrative, which ensures long-range coherence in both the storyline and visual a…

Cited by 0SourceScholar
2026

Captain Safari: A World Engine with Pose-Aligned 3D Memory

CVPR 2026

World engines aim to synthesize long, 3D-consistent videos that support interactive exploration of a scene under user-controlled camera motion. However, existing systems struggle under aggressive 6-DoF trajectories and complex outdoor layouts: they lose long-range geometric coherence, deviate from t

Cited by 0SourcecodeScholar
2026

Mixture of Contexts for Long Video Generation

ICLR 2026poster

Long video generation is fundamentally a long context memory problem: models must retain and retrieve salient events across a long range without collapsing or drifting. However, scaling diffusion transformers to generate long-context videos is fundamentally limited by the quadratic cost of self-atte…

Cited by 0SourceScholar
2026

Play to Generalize: Learning to Reason Through Game Play

ICLR 2026poster

Developing reasoning capabilities in multimodal large language models (MLLMs) remains challenging. Motivated by literature suggesting that gameplay promotes transferable reasoning skills, we propose a novel post-training method, Visual Game Learning (ViGaL), where MLLMs develop generalizable reasoni…

Cited by 0SourcecodeScholar
2025

VideoAuteur: Towards Long Narrative Video Generation

ICCV 2025poster

Recent video generation models have shown promising results in producing high-quality video clips lasting several seconds. However, these models face challenges in generating long sequences that convey clear and informative events, limiting their ability to support coherent narrations. In this paper…

Cited by 0SourcePDFScholar
2025

Vision‑Language‑Vision Auto‑Encoder: Scalable Knowledge Distillation from Diffusion Models

NeurIPS 2025poster

Building state-of-the-art Vision-Language Models (VLMs) with strong captioning capabilities typically necessitates training on billions of high-quality image-text pairs, requiring millions of GPU hours. This paper introduces the Vision-Language-Vision **(VLV)** auto-encoder framework, which strategi…

Cited by 0SourceScholar
2025

What If We Recaption Billions of Web Images with LLaMA-3?

ICML 2025poster

Web-crawled image-text pairs are inherently noisy. Prior studies demonstrate that semantically aligning and enriching textual descriptions of these pairs can significantly enhance model training across various vision-language tasks, particularly text-to-image generation. However, large-scale investi…

Cited by 38SourcePDFScholar
2024

A Semantic Space is Worth 256 Language Descriptions: Make Stronger Segmentation Models with Descriptive Properties

ECCV 2024poster

"We introduce ProLab, a novel approach using property-level label space for creating strong interpretable segmentation models. Instead of relying solely on category-specific annotations, ProLab uses descriptive properties grounded in common sense knowledge for supervising segmentation models. It is…

2024

Rejuvenating image-GPT as Strong Visual Representation Learners

ICML 2024oral

This paper enhances image-GPT (iGPT), one of the pioneering works that introduce autoregressive pretraining to predict the next pixels for visual representation learning. Two simple yet essential changes are made. First, we shift the prediction target from raw pixels to semantic tokens, enabling a h…

2023

CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection

ICCV 2023poster

An increasing number of public datasets have shown a marked impact on automated organ segmentation and tumor detection. However, due to the small size and partially labeled problem of each dataset, as well as a limited investigation of diverse types of tumors, the resulting models are often limited…

Cited by 230PDFcodeScholar
2023

Label-Free Liver Tumor Segmentation

CVPR 2023poster

We demonstrate that AI models can accurately segment liver tumors without the need for manual annotation by using synthetic tumors in CT scans. Our synthetic tumors have two intriguing advantages: (I) realistic in shape and texture, which even medical professionals can confuse with real tumors; (II)…

2023

Masked Autoencoders Enable Efficient Knowledge Distillers

CVPR 2023poster

This paper studies the potential of distilling knowledge from pre-trained models, especially Masked Autoencoders. Our approach is simple: in addition to optimizing the pixel reconstruction loss on masked inputs, we minimize the distance between the intermediate feature map of the teacher model and t…

2022

Learning From Temporal Gradient for Semi-Supervised Action Recognition

CVPR 2022poster

Semi-supervised video action recognition tends to enable deep neural networks to achieve remarkable performance even with very limited labeled data. However, existing methods are mainly transferred from current image-based methods (e.g., FixMatch). Without specifically utilizing the temporal dynamic…

Cited by 88PDFcodeScholar
2019

A bio-robotic remora disc with attachment and detachment capabilities for reversible underwater hitchhiking

ICRA 2019poster

Remoras employ their adhesive discs to rapidly attach to and detach from a wide range of marine surfaces. By analyzing high-speed images of remoras' (Echeneis naucrates) hitchhiking behavior, we describe the fish's detachment mechanism as a lip curling up to break the seal between the disc and subst…

Cited by 9SourceScholar