Motion control is crucial for generating expressive and compelling video content; however,
most existing video generation models rely mainly on text prompts for control, which struggle …

While recent foundational video generators produce visually rich output, they still struggle
with appearance drift, where objects gradually degrade or change inconsistently across …

Understanding the ability of humans to use objects is crucial for AI to improve daily life.
Existing studies for learning such ability focus on human-object patterns (eg, contact, spatial …

Predicting the dynamics of interacting objects is essential for both humans and intelligent
systems. However, existing approaches are limited to simplified, toy settings and lack …

Interactive image editing allows users to modify images through visual interaction operations
such as drawing, clicking, and dragging. Existing methods construct such supervision …

Crafting magic and illusions is one of the most thrilling aspects of filmmaking, with visual
effects (VFX) serving as the powerhouse behind unforgettable cinematic experiences. While …

In this paper, we consider the problem of long-term point tracking, which requires consistent
identification of points across multiple frames in a video, despite changes in appearance …

In this paper, we present TAPTRv3, which is built upon TAPTRv2 to improve its point
tracking robustness in long videos. TAPTRv2 is a simple DETR-like framework that can …

Robot foundation models, particularly Vision-Language-Action (VLA) models, have
garnered significant attention for their ability to enhance robot policy learning, greatly …

Point tracking in videos is a fundamental task with applications in robotics, video editing, and
more. While many vision tasks benefit from pre-trained feature backbones to improve …